Miracle-dz/UniFAR-FTUs huggingface dataset:
ON THE PROBABILISTIC SEISMIC HAZARD ESTIMATE FOR HUSAVIK, NORTH ICELAND, ON THE BASIS OF MONTE CARLO METHODS

Húsavík, the second largest town in North Iceland, is effectively located, directly on top of the Húsavík–Flatey Fault (HFF), the largest transform fault in Iceland. The diverse geology and topography under the town is likely to contribute to localized differences in site effects and spatially variable earthquake strong-motions, indicating significant relative differences in seismic risk to its inhabitants. Previous earthquake hazard estimates of this region have relied on a single ground motion model and incorporated uncertainties in a limited way, but pointing out several ways to improve the hazard estimates. In this paper, a probabilistic seismic hazard analysis (PSHA) of the area of Húsavík in terms of peak ground acceleration (PGA) and spectral accelerations (SA) is presented using the Monte-Carlo (MC-PSHA) and Cornell-McGuire (CM-PSHA) methods, respectively. We considered different ground-motion models and selected the best model based on data-driven approaches. Both aleatory and epistemic uncertainties are taken into account. Moreover, the disaggregation of the seismic hazard is carried out to identify hazard-dominating events. The presented results shed further light on the earthquake hazard of Húsavík with implications for the associated seismic risk.
A Bayesian model for RTS units control applied to StarCraft

In real-time strategy games (RTS), the player must reason about high-level strategy and planning while having effective tactics and even individual units micro-management. Enabling an artificial agent to deal with such a task entails breaking down the complexity of this environment. For that, we propose to control units locally in the Bayesian sensory motor robot fashion, with higher level orders integrated as perceptions. As complete inference encompassing global strategy down to individual unit needs is intractable, we embrace incompleteness through a hierarchical model able to deal with uncertainty. We developed and applied our approach on a StarCraft1 AI.
Compressed Sensing and the Quadratic Bottleneck Problem: A Combinatorics Approach

Compressed sensing is the study of solving underdetermined systems of linear equations with unique sparse solutions. In addition to this, applications of compressed sensing require that the number of rows of the measurement matrix is minimized. In general, the entries of a measurement matrix can be complex. A combinatorial measurement matrix narrows this down to just zeros and ones. These measurement matrices may be obtained from other objects such as the incidence matrix of a combinatorial design or the bipartite adjacency matrix of a bipartite graph. In many applications, a measurement matrix is normally a randomly constructed matrix. This is because it has been shown that with high probability, certain classes of random measurement matrices have on the order of the optimal number of rows required for sparse reconstruction. Finding deterministically constructed classes of measurement matrices whose number of rows scale on the same order as classes of random measurement matrices has been an open problem for at least a decade. This problem is referred to as the quadratic bottleneck problem. The quadratic bottleneck problem is important for several di erent reasons. A speci c randomly generated measurement matrix cannot be checked if it does indeed recover every sparse vector uniquely. An engineer developing a sensor system might nd it undesirable or not possible to implement a physical system that can take random measurements. Recovery algorithms may be developed for a speci c class of deterministically constructed measurement matrices. Or, it could just be considered a proof of concept that it can be done. The goal of this thesis is to de ne the su cient compressed sensing theory, graph theory, and combinatorial design theory to attempt an answer at the quadratic bottleneck problem with combinatorial measurement matrices. After this, an attempt to de ne a solution to the quadratic bottleneck problem and describe a valid argument that could be used to demonstrate this is made. Finally, a selection of common compressed sensing recovery algorithms are selected and optimized for these explicit constructions.
Contrast Enhancement of Chest X-Ray Images by Automatic Scoring

This study aimed to automatic scoring of performance test in conventional diagnostic x-rays where its done in alkuity hospital and Dar alelag specialized hospital, to measure the resolution, contrast, noise and signal to noise ratio with different exposure factors, highlight the importance of the Quality Control (QC) methods in ensuring that a product complies with all the requirements and specifications laid out for it, enhance the X.ray image quality using different spatial and frequency domain filters and to optimize the exposure factors with patient body characteristics (gender, age, weight, height). patients sample was 100 their aged ranged from 18-70 years with chest X.ray. The study results in enhancement of image quality by increasing the resolution, contrast, signal to noise ratio with different exposure factors, and to optimize the exposure factors with patient body characteristics which lead to avoid image repeating for the patient and minimizing the cost for both patient and hospitals. Key wards: Automatic Scoring, Enhancement performance, chest, X-ray, -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 11-07-2018 Date of acceptance: 27-07-2018 -------------------------------------------------------------------------------------------------------------------------------------
DAMAGE DETECTION IN A STRUCTURAL SYSTEM VIA BLIND SOURCE SEPARATION

A technique for vibration based system identification for detection of earthquake induced damage in structural systems is discussed. A numerical case study of detection of damage in a building frame subjected to a strong earthquake is presented for the application of a blind source separation algorithm to the problem of output only modal identification. The problem of base-excitation, as in earthquake loading, presents a situation wherein the governing equation of motion is usually formulated in terms of the deformations relative to the base motion whereas the response recordings are of absolute acceleration. The conditions under which the blind source separation formulation of representing observed system response as a mixture of independent sources can be adapted for the case of base excited systems are discussed. The modal parameters (mode shapes, natural frequencies,) are extracted from the vibration response and the changes in the identified modal parameters are tracked in time through a moving time-window analysis. The implications of the assumptions in the formulation and their validity in practical problems is also discussed.
Shift Work Disorder and Associated Health Problems among Doctors in a Tertiary Teaching Care Hospital, Andhrapradesh

Introduction: Shift work disorder(SWD) is a circadian rhythm sleep disorder characterized by insufficient or excessive sleepiness occuring in people whose work hours coincide with the typical sleep period.A shift worker is anyone who follows a work schedule that is outside of typical 9am to 5pm business day. Objective: To assess the prevalence of SWD and other related health problems among doctors in a government established tertiary teaching care hospital. Materials And Methods: Arandomised prospective study was conducted in a tertiary care teaching hospital,tirupati, andhrapradesh for 3months ,that is from august to October,2019.A total of 150 doctors were randomly selected. Informed consent was taken from the participants. They were given two questionnaires which include “standard shift work index questionnaire”(SSWIQ) and “Bergen shift work sleep questionnaire(BSWSQ)”. Each questionnaire contains a battery of relatedquestions. Both the indices were analysedstatiscally. Results: The prevalence of SWSD is about 24.6%according to SSWIQ and about 28.6% according to BSWSQ. We found that there was no significant association between the presence of SWD according to SSWIQ and BSWSQ. (P=0.43). Fatigue(80%) was the most common complaint among other correlated health problemsfollowedby backache ,epigastricpain, headacheand menstrual irregularities. Conclusion: The study showed increase in SWD in shift workers. This can be minimized by rotating shift every 2 weeks,maximizing leisure time,exposure to bright light and melatonin treatment.However if SWSD is severe it is advised to take medications that promote alertness like caffeine ,modafinil and armodafinil which have been approved by FDA. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 01-01-2020 Date of Acceptance: 16-01-2020 -------------------------------------------------------------------------------------------------------------------------------------
Analysis of reporting behavior using the hopit package

Self-reported health, happiness, attitudes, and other statuses or perceptions are often the subject of biases that may come from different sources. For example, the evaluation of an individual’s own health may depend on previous medical diagnoses, functional status, and symptoms and signs of illness; as on well as life-style behaviors, including contextual social, gender, agespecific, linguistic and other cultural factors (Jylha 2009; Oksuzyan et al. 2019). The hopit package offers versatile functions for analyzing different self-reported ordinal variables, and for helping to estimate their biases. Specifically, the package provides the function to fit a generalized ordered probit model that regresses original self-reported status measures on two sets of independent variables (King et al. 2004; Jürges 2007; Oksuzyan et al. 2019). The first set of variables (e.g., health variables) included in the regression are individual statuses and characteristics that are directly related to the self-reported variable. In the case of self-reported health, these could be chronic conditions, mobility level, difficulties with daily activities, performance on grip strength tests, anthropometric measures, and lifestyle behaviors. The second set of independent variables (threshold variables) is used to model cut-points between adjacent self-reported response categories as functions of individual characteristics, such as gender, age group, education, and country (Oksuzyan et al. 2019). The model helps to adjust for specific socio-demographic and cultural differences in how the continuous latent health is projected onto the ordinal self-rated measure. The fitted model can be used to calculate an individual predicted latent status variable, a latent index, and standardized latent coefficients; and makes it possible to reclassify a categorical status measure that has been adjusted for inter-individual differences in reporting behavior.
SEISMIC RESPONSE OF STEPPED BUILDING SUPPORTED BY STEPPED FOUNDATION ON HILLSIDE

The step back-set back building is supported by stepped foundation where the foundation elevation and roof elevation are different. The complexity of seismic input of stepped site and the irregularity of this building make seismic response of this structure has its own particularity. In this paper, a model of identical inputting wave and a model of soil-structure interaction suitable for seismic response of step back-set back buildings were developed. The dynamic response of this structure, i.e. period, storey drift, storey shear, and the shear distribution characteristic of columns have been studied by using elastic seismic response analysis method. The distribution of plastic hinges and the yield mechanism of the structures were studied by using elastoplastic analysis method. Some suggestions on seismic design for step back-set back building were presented. The conclusion will be beneficial to improve the seismic resistance capability, and promote the application of step back-set back building.
How Individuals Influence Supply Chain Management Performance?

Supply chain management has been an important field in business operations. Due to the popularity of electronic commerce and mobile commerce, the supply chain field has been evolved to another level. Higher level of automation and use of computerized software have been deployed. Human intervention still cannot be avoided. Rather, human interactions play an important role streamlining the supply chain processes. Both individual and group human performances thus draw much attentions in the success of supply chain applications. However, little is known about the individual’s contribution to the performance in the field. This study aims to understand the individuals’ performance based on their individual personality traits. Attribute selection methods are used to identify the key personality traits in the Big Five Model.
Thyroid Disease andDiabetes

This study was carried out to estimate thyroid hormones (T3, T4 and TSH) level in diabetic patients and to compare it with normal controls in an attempt to find out the importance of thyroid hormone estimation in diabetic cases. Fifty cases of diabetes mellitus who attended Diabetic Clinic, J.L. N.M. CH , Bhagalpur during the period from October 2016 to March 2017 were taken as the cases and 50 healthy individuals were selected as control group. Serum total Tri-iodothyronine (T3), Thyroxine (T4), Thyroid stimulating hormone and blood sugar were estimated in both the cases and controls. The study showed that diabetes was more prevalent in the age group of 51-65 years, and more in males (52%). The mean fasting blood sugar (182.12 ± 30.28mg%) and serum TSH level (8.54 ± 1.07mIU/L) were increased significantly (r=0.884, p>0.05) whereas serum T4 level (2.21± 0.55μg/dl) was decreased in diabetic cases when compared with controls.Mean T3 level of diabetic cases was higher than controls but it was insignificant. Diabetes mellitus cases with statistically significant higher TSH value have more prevalence of complications like hypertension, retinopathy, nephropathy etc. A statistically significant, negative correlation (r=-0.942, p<0.05) was seen between Serum T4 and blood sugar in the cases.Therefore routine screening of thyroid hormone level in addition to other biochemical tests in the early stage of diabetes will help better in the management of thease patients. --------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 10-04-2018 Date of acceptance: 24-04-2018 --------------------------------------------------------------------------------------------------------------------------------------
Rapid progressive anti-GBM glomerulonephritis with multiple auto-antibodies

Rapidly progressive glomerulonephritis (RPGN) is a clinical syndrome manifested by progressive loss of renal function in a short period. At renal biopsy, it is characterized by crescent formation. RPGN may be associated with the presence of circulating antibodies. We report a case of type IV RPGN [ANCA and Anti–glomerular basement membrane (anti-GBM) antibody disease], a severe disease causing a difficult to treat picture. Our case was complicated by severe thrombocytopenia due to the use of heparin and later on by thrombotic microangiopathy. These events occurred rapidly, making the clinical framing and management decisions very hard.
AAV-mediated gene transfer to synovium: enhancing effects of inflammatory cytokines and proteasome inhibitors

Rheumatoid arthritis (RA) is an autoimmune disease affecting nearly 1% of the population. The joints of RA patients become inflamed and a pannus of synovial tissue invades cartilage and destroys bone. Current treatments, though moderately successful, are often administered systemically and are associated with significant side effects. Local treatment of arthritis by intra-articular injection of gene transfer vectors has the potential to overcome some of the obstacles of other treatment regimens. In particular, adeno-associated virus (AAV) is attractive as a gene transfer vector because it is non-pathogenic in humans, has low immunogenicity and broad tissue tropism, and provides for long-term transgene expression. The primary target of gene transfer in the joint is the fibroblast-like synoviocytes (FLS), which make up part of the pannus of tissue responsible for cartilage and bone destruction. However, FLS are only minimally transduced by AAV and provide only low levels of transgene expression. For local treatment with AAV vectors to be successful, improvement in the transduction of FLS is necessary. Several agents have been shown to increase AAV transduction in other cell types. The specific effect of inflammation and proteasome inhibition on AAV-mediated transgene expression in FLS has not been examined. Here we show that both inflammatory cytokines and the proteasome inhibitor zLLL can increase transgene expression in FLS dramatically. Remarkably, both agents are also able to regulate transgene expression. The cytokines appear to act in part by promoting uncoating of the virus, while proteasome inhibition works by both increasing the nuclear trafficking of the virus and by increasing transcription of the viral DNA. In addtion, we screened 3 serotypes of AAV (2, 2.5, and 5) for their ability to transduce FLS from 4 different species: human, mouse, horse, and rabbit. AAV2 provided the highest transgene expression in human and horse FLS, while AAV2.5 was better suited for mouse and rabbit FLS. These results have implications in the future use of AAV vectors in the treatment of RA.
ADJUSTING PORTFOLIO LOSS ESTIMATES IN LIGHT OF UPDATE TO THE EARTHQUAKE HAZARD MODEL IN CALIFORNIA

This study presents two heuristic approaches to adjust the California earthquake occurrence rates in the commercial catastrophe models based on the new Uniform California Earthquake Rupture Forecast (UCERF3) time-dependent model. The UCERF3 model was developed by the 2014 Working Group on California Earthquake Probabilities and incorporates updated earthquake catalogs, new smoothed seismicity algorithms and inputs, combined fault and geodetic based slip-rate models, and more comprehensive earthquake rupture models. The time-dependent (TD) rates in UCERF3 reveal significant model changes compared to the previous forecast (UCERF2) upon which the current catastrophe earthquake loss models for the United States are developed. Changes partly originate from the inclusion of multifault ruptures, where earthquakes are no longer confined to separate, individual faults, but rather can occasionally rupture multiple faults simultaneously. The impact of model changes in terms of earthquake rates –including multifault rupture effects– on the projected short-term and long-term modeled losses for selected portfolios in the United States are estimated in this study. Two rate adjustment approaches are examined: (1) uniform application of the averaged earthquake rate changes over all groups of faults in different regions of California; and (2) application of fault-by-fault rate adjustment for each event within the catastrophe models’ stochastic event sets. The results from two approaches are compared by performing a set of sensitivity tests on portfolio level loss estimates. The second approach directly employs the multifault rupture effects and is shown to be more reliable to estimate the projected loss changes.
Seismic Performance Evaluation of Damaged RC column Retrofitted by GFRP- Strip Device

Many reinforced concrete (RC) buildings, which were designed and constructed with old seismic-design codes, have been seriously damaged and destructed in both destructive earthquakes and several aftershocks. Several aftershocks may be quite destructive because of the previous damage of the RC building. Therefore, demand for development of rapid-repair methods was increased to prevent possible collapse of RC building during the aftershocks. Partial or total collapse of a RC building under the earthquakes was led by the collapse of columns. Therefore, the main purpose of a seismic retrofitting method is to increase shear capacity of the RC columns. In this study, a GFRP-strip device was proposed to improve the seismic performance of damaged RC columns and was designed to consider easy installation and rapid repair. The GFRP-strip device consists of both GFRP composite strips and aluminum clip-connectors. The shape of the aluminum clip-connectors was designed in three pieces to consider easy installation and rapid repair. Three RC specimens consisted of two columns, which were designed at 75% scale of existing school buildings constructed in the 1980s in South Korea, and were constructed to evaluate the performance of the GFRP-strip device. Two of the RC specimens were pre-tested to take damage before installing the GFRP-strip device. After the pre-test damage was done, the GFRP-strip devices were installed along the plastic-hinge regions on both ends of the test columns. The experimental test results indicate several improvements in seismic performance of damaged columns. These include strength enhancement, failure mode, ductility and hysteretic energy-dissipation capacity. Thus, both the maximum strength and ductility of the retrofitted specimens were increased. Furthermore, accumulated energy-dissipation capacity of the retrofitted specimens was increased. Taking the un-retrofitted RC specimen as a control specimen, the failure behavior of the retrofitted RC specimens was changed from brittle-shear failure to ductile-flexural behavior, which was maintained until the failure of the GFRP-strip devices occurred. Finally, it is shown that the proposed GFRP-strip device developed can be used to improve the seismic performance of damaged RC columns.
Sentiment Features based Analysis of Online Reviews

: Sentiment Analysis (SA) and Summarization is a new and emerging field of research which deals with information extraction and knowledge discovery from text using Natural Language Processing and Data Mining technique, which help to track the mood of public about specific products and social or political event. Sentiments of individuals are extremely useful for people and company owner for making several decisions. However decision based upon some of the online review among the large set of review are not very easy for classifying the sentiment. This report introduce new Hybrid Polarity Detection System for SA of short informal text i.e. Twitter post to compare with state-of-art method which used as analysis of Sentiment Summarization. Additionally proposed Hybrid Polarity Detection System derives high performance with new set of features.