Miracle-dz/UniFAR-FTUs huggingface dataset:
CLINICOHEMATOLOGICAL PROFILES OF HEPATITIS A VIRUS ( HAV ) : A RETROSPECTIVE STUDY

Aim: Acute viral hepatitis A (HAV) is a major problem in parts of the developing countries. HAV is transmitted enterically and its incidence is high in places where poor hygienic conditions prevail. Most studies in the past have been on liver the primary organ affected by HAV and reports on extrahepatic organs are lacking. The present study was carried out to ascertain the alterations on the haematological, hepatic and renal parameters. Material and Methods: This was a retrospective study and was conducted in a tertiary care hospital in India. Data was analysed in people who expressed known symptoms of HAV and established by Anti-HAV IgM antibody. A total of 22 paediatric and 109 adult people were included in the study and compared with healthy individuals who were tested negative for infectious and chronic diseases. Results: The results indicated that jaundice, vomiting and fever were the predominant clinical symptom seen in both children and adults. There was significant difference in the various haematological, hepatic and electrolyte endpoints (p < 0.05 to 0.0001), while there was no such difference in the renal function test parameters. Conclusion: The present study indicates that acute infection with HAV causes alterations in haematological, hepatic parameters and in the levels of electrolytes in the serum.
Acoustic Scene Classification Using SpecAugment and Convolutional Neural Network with Inception Modules Technical Report

This paper describes the system submitted to the Task 1a (Acoustic Scene Classification, ASC). By analyzing the major systems submitted in 2017 and 2018, we have selected a two-dimensional convolutional neural network (CNN) as the most suitable model for this task. The proposed model is composed of four convolution blocks; two of them are conventional CNN structures but the following two blocks consist of Inception modules. We have constructed a meta-learning problem with this model in order to train the super learner. For each base model training, we have applied different validation split methods to take advantage in generalized result with the ensemble method. In addition, we have applied data augmentation in real time with SpecAugment, which was performed for each base model. With our final system with all of the above techniques have applied, we have achieved an accuracy of 76.1% with the development dataset and 81.3% with the leader board set.
Annoyance potential of wind turbine noise compared to road traffic noise

The production of wind energy is becoming increasingly important worldwide, with the result that greater numbers of the population are being exposed to wind turbine noise. There is evidence that wind turbine noise has a high annoyance potential, which might be caused by specific sound characteristics such as amplitude modulation. Compared to road traffic noise, however, knowledge of the annoyance effects of wind turbine noise remains scarce. In this study, the annoyance of wind turbine noise and road traffic noise were investigated and compared. To that aim, listening tests were done in the laboratory, allowing controlled experimental conditions and the exclusion of potential effect modifiers such as the visual appearance of wind turbines in field surveys. For the listening tests, specific sound scenarios were generated, either by sound synthesis (wind turbine noise) or by mixing of single pass-by recordings (road traffic noise). The set of sound scenarios enabled auralisation of variations of three variables potentially influencing annoyance, namely source type (wind turbine, road traffic), sound pressure level, and temporal level variation (without, periodic, or random variation). Subjects were exposed to these different sound scenarios, and their ratings on subjectively perceived annoyance were collected. The factorial design of the experiment allows separating the individual contributions of the above three variables to the annoyance ratings. Here, the setup of the listening tests, the most important results and possible applications in environmental impact assessment are presented.
Global wavefront sensing for Extremely Large Telescopes

In ELTs the larger size of the aperture will translates into different categories of problems and different kind of solutions. The concept of Global Multi Conjugated Adaptive Optics is here introduced. In this, the wavefront sensing is extended to a much larger Field of View, practically limited by the telescope optics or optomechanics and by the limit given by the coverage of the metapupil at the highest altitude of interest. The correction of these layers is employed in a numerical fashion and the information is retrieved in order to compensate for a much limited Field of View. All this, being done in a layer oriented fashion, does allow for a simplified treatment of the Signal to Noise Ratio and to an estimate of the performances in the plot h vs. spatial scales where layers and the related Kolmogorov distributed turbulence are plotted. Once this information is retrieved it is fed back into the existing Deformable Mirror with a back-projection that allow for the most efficient way in terms of coverage of the spatial frequencies. The nature of the closedvs open-loop of such an approach is also briefly discussed. The aim of a sky coverage and of performances getting closer or exceeding the ones provided by Laser Guide Stars can be at hands.
Learning Scene Geometry for Visual Localization in Challenging Conditions

We propose a new approach for outdoor large scale image based localization that can deal with challenging scenarios like cross-season, cross-weather, day/night and long-term localization. The key component of our method is a new learned global image descriptor, that can effectively benefit from scene geometry information during training. At test time, our system is capable of inferring the depth map related to the query image and use it to increase localization accuracy. We are able to increase recall@1 performances by 2.15% on cross-weather and long-term localization scenario and by 4.24% points on a challenging winter/summer localization sequence versus state-of-the-art methods. Our method can also use weakly annotated data to localize night images across a reference dataset of daytime images.
An autopsy case of widespread brain dissemination of glioblastoma unnoticed by magnetic resonance imaging after treatment with bevacizumab

Background: Although glioblastoma has been shown to be able to disseminate widely in the intracranially after treatment with bevacizumab without any significant radiological findings, reports on such cases with subsequent autopsy findings are lacking. Case Description: A 36-year-old man presented with a general seizure and a mass of the right frontal lobe, which was diagnosed as diffuse astrocytoma (WHO Grade II). The patient underwent a total of four surgeries from 2005 to 2017. He showed tumor recurrence, progression, and malignant transformation to glioblastoma (GBM) (WHO Grade IV) despite repeated tumor resections, radiotherapy, and chemotherapies with temozolomide and carmustine wafers. Bevacizumab (10 mg/kg body weight) was started following the fourth surgery. After bevacizumab administration, the patient’s clinical condition improved to a Karnofsky performance status (KPS) score of 50–60, and he was stable for several months before finally deteriorating and passing away. Although sequential magnetic resonance imaging (MRI) showed shrinkage of the lesion and a reduction of edema, an autopsy showed widespread tumor invasion that was not revealed on MRI. Neoplastic foci were identified extensively in the cerebral cortex, basal ganglia, pituitary gland, cerebellum, and brainstem, imposing as gliomatosis cerebri. Conclusion: Imaging follow-up of malignant gliomas needs to be interpreted with caution as marked improvement in radiological response after bevacizumab treatment may not be indicating tumor regression. Despite the notable lack of evidence to increase overall survival in GBM patients with bevacizumab, the increase in progression-free survival and the observed relief of symptoms due to a decrease in edema should be considered relevant for patient management.
Inverse Reinforcement Learning for Dynamics by

Inverse Reinforcement Learning for Dynamics by McKane Andrus Master of Science in Electrical Engineering and Computer Science University of California, Berkeley Professor Anca Dragan, Chair Inverse Reinforcement Learning (IRL), as standardly defined, entails learning an unknown reward function of a Markov Decision Process (MDP) from demonstrations. As Herman et al. [10] describe, however, learning a reward function from demonstrations is highly reliant on having a correct transition function, which is not always a given. We take interest in this problem from the perspective of Human-Robot Interaction, where we can often observe demonstrations of known tasks but do not have a necessarily correct model of human capability. As such, we specifically consider the case where the goal, or reward, of the demonstrations is known, but the dynamics, or transition function, are not. We refer to this alternate formulation as Inverse Reinforcement Learning for Dynamics (IRLD). In Chapter 2 we formalize the IRLD problem statement and provide a method that is able to learn unobserved dynamics in environments of limited size and scope. We compare this method to one that estimates both the reward and the dynamics to show the advantages of incorporating knowledge of a goal. In Chapter 3 we propose an alternate, scalable approach to the IRLD problem statement that permits numerous variants of Maximum Likelihood Estimation algorithms using function approximators. Though we were not able to produce a generally applicable method, in chapter 4 we provide a roadmap of the various algorithms we developed and issues that must be addressed for this approach to succeed in future work. Chapter 5 contains a reflection section where our work is positioned in a broader social context.
6 . 2 TESTING THEORIES OF THE ANTARCTIC CIRCUMPOLAR CURRENT AGAINST OBSERVATIONS

The Antarctic Circumpolar Current (ACC) dominates the dynamics of the Southern Ocean and plays a critical role in the global ocean circulation. While the ACC connects the ocean basins, it isolates the polar region since, by simple de nition, the mean circumpolar ow cannot transport quantities poleward. (see streamlines on Fig. 1). Yet the ocean remains in a quasi-steady state, indicating that other processes transport quantities across the ACC to balance di erential surface forcing. The dominant forcing of the ACC is the strong westerly winds, the roaring forties, that blow over it. At the same time as the wind drives the ACC's eastward ow, it also drives an overturning cell|the Deacon Cell|associated with Ekman processes: uid upwells in the south, travels northward at the surface, and is pumped to depth in the subtropics. The northward Ekman transport carries heat northward, requiring a balancing southward cross stream transfer of heat. This compensating ux is supplied by baroclinic eddies that feed o the potential energy in the strati cation of the ACC. Mooring data have established that the poleward eddy heat ux is su cient to balance the Ekman ux (Phillips and Rintoul, 2000). The atmosphere also forces the ACC through surface buoyancy uxes. The Southern Ocean is a region of signi cant heat loss and gain at ocean surface and strong surface salinity uxes associated with evaporation and precipitation in the north and ice formation and melt in the south. These buoyancy uxes are balanced by the residual circulation|the small imbalance between the eddies and the winds. In previous work we examined how the balance between eddy transport and surface wind and buoyancy forcing set the strati cation and transport of an idealized circumpolar current; see Marshall et al. (2001), Karsten et al. (2001). We discussed the implications of this balance on the dynamics of the ACC in Karsten and Marshall (2001). Here, guided by our previous work, we describe our attempts to diagnose from observations the meridional overturning of the ACC. We show
Effect of Using Anise Seeds Powder as Natural Feed Additive on Performance and Carcass Quality of Broiler Chicks

The effect of feeding broiler chicks on diets conta i ing different levels of anise seeds powder as nat ural feed additive on productive performance, carcass charact eristics and economic efficiency were studied. A to tal f two hundred one-day old, unsexed (Ross-308) broiler chi cks were randomly divided into four experimental gr oups. Each group was further subdivided into five replicates a t the rate of ten chicks per pen in complete random ized design. The birds were fed with two basal diets (starter an d fi isher diets). The anise seeds powder ( Pimpinella anisum L.) was added to the basal diets at level (0.0, 0.5, 0. 75 and 1%) resulting in four formulae respectively to group A, B, C and D with group A serving as control group. The ex perimental diets were fed for 6-weeks duration. Hea lth of the stock and performance parameters was recorded. At t he end of the experiment, the birds were slaughter, dr ssing then used for different parameters and economical e valuation were calculated. The results showed that, e diet with 1% anise seeds powder had significantly (P<0.05) he aviest body weight gain, highest feed intake, best f ed conversion ratio, and highest dressing percentage w ith the highest percentage of commercial cuts (brea st drumstick and thigh). In addition to, the inclusion of anise seeds powder in broiler diets showed significantly (P<0.05) the most tender breast and thigh meat and higher liver perce ntag as compared to control diet. The birds fed wi th the control diet produced significantly (P<0.05) highest abdomi nal fat percentage. The mortality rate was not sign ificantly (P>0.05) affected by the addition of anise seeds po wder to broiler diets. The highest profitability ra tio (1.52) was obtained by the diet with 1% anise seeds powder in b oiler diet.
Evaluation of Antibacterial , Antioxidant and Antiobese Activities of the Fruit Juice of Crabapple Mangrove Sonneratia caseolaris ( Linn . )

A study was carried out to investigate the antibacterial, antioxidant, and antiobese activities of fruit juice of the mangrove plant Sonneratia caseolaris. The fruit juice was prepared by three different methods: water extract of fruit flesh (J1), hot water extract of fruit flesh (J2), and hot water extract of whole fruit (J3). All three juice samples exhibited antibacterial and antioxidant activities, and sample J3 showed the highest activities compared with sample J1 and J2. Sample J3 was then chosen for an antiobese activity test. The results demonstrated that the crabapple mangrove fruit juice had an effect to prevent the increase in body weight of the mice. The study suggests fruit juice of S. caseolaris as a potential source of active compounds with antimicrobial, antioxidative, and antiobesity properties and can be used as natural antibacterial, antioxidative, and antiobesity agents in pharmaceutical and food industries.
A Note on the Misinterpreted Twin Decomposition

The classical twin model has often been used to determine whether variation in outcomes such IQ, schooling and other behavioral traits, originate from genetic endowments or environmental factors. Despite some heavy criticism from prominent scholars, the model has recently reappeared in highly ranked economics journals to perhaps spark off a revival of the method. This article seeks to specify the assumptions which generate the apparently profound divide in viewpoints. A general problem is that most authors do not properly discuss the underlying assumptions of the twin model. It has partly led to a disarray of thoughts, concrete examples are provided, since the interpretation of the results and the risk for misleading interpretations are not spelled out. Therefore, perhaps surprisingly, a brief account of the theories behind the main assumptions of the twin model provides a useful contribution. JEL codes: genes, environments
A Decision Support Tool for Video Retinal Angiography 2018

Fluorescein angiogram (FA) is a medical procedure that helps the ophthalmologists to monitor the status of the retinal blood vessels and to diagnose proper treatment. This research is motivated by the necessity of blood vessel segmentation of the retina. Retinal vessel segmentation has been a major challenge and has long drawn the attention of researchers for decades due to the presence of complex blood vessels with varying size, shape, angles and branching pattern of vessels, and non-uniform illumination and huge anatomical variability between subjects. In this thesis, we introduce a new computational tool that combines deep learning based machine learning algorithm and a signal processing based video magnification method to support physicians in analyzing and diagnosing retinal angiogram videos for the first time in the literature. The proposed approach has a pipeline-based architecture containing three phases image registration for large motion removal from video angiogram, retinal vessel segmentation and video magnification based on the segmented vessels. In image registration phase, we align distorted frames in the FA video using rigid registration approaches. In the next phase, we use baseline capsule based neural networks for retinal vessel segmentation in comparison with the state-of-the-art methods. We move away from traditional convolutional network approaches to capsule networks in this work. This is because, despite being widely used in different computer vision applications, convolutional neural networks suffer from learning ability to understand the object-part relationships, have high computational times due to additive nature of neurons and, loose information in the pooling layer. Although having these drawbacks, we use deep learning methods like U-Net and Tiramisu to measure the performance and accuracy of SegCaps. Lastly, we apply Eulerian video magnification to magnify the subtle changes in the retinal video. In this phase, magnification is applied to segmented videos to visualize the flow of blood in the retinal vessels.
Some Observations on the Predominance of Aphis spiraecola on Citrus in Northwestern Algeria

Labdaoui, Z.E. , and Guenaoui, Y. 2018. Some observations on the predominance of Aphis spiraecola on citrus in Northwestern Algeria. Tunisian Journal of Plant Protection 13 (si): 147-157. Aphis spiraecola is the main aphid species found on citrus in Algeria. This study was carried out on Citrus clementina in northwestern Algeria, during a two year period (2016-2017) in the first flushing period (spring). The aphid fluctuation of the populations and their natural enemies, especially the parasitoids, were evaluated based on a weekly sampling of 100 leaves taken on 10 trees (10 leaves/ tree). A. spiraecola colonized citrus trees since the beginning of flushing. The density per young leaf reached a maximum of 78.8 ± 23.4 aphids in 2016 and 44.4 ± 13.0 aphids in 2017 with an average density of 6.0 ± 1.5 aphids/cm2 and 4.4 ± 0.6 aphids/cm2, respectively, where a significant difference between years (P < 0.05) was observed. The parasitism rate expressed in terms of number of A. spiraecola mummies remained very low, varying between 1.6% in 2016 and 3.0% in 2017 with no significant difference (P > 0.05) between years. Also, the emergence number of primary parasitoids was low for both years with 26.6% in 2016 and 10.8% in 2017. The primary parasitoids of A. spiraecola in 2016 were Lysiphlebus testaceipes and Binodoxys angelicae whereas only L. testaceipes was found in 2017. The total hyperparasitism rate varying between 16.7% in 2016 and 25.7% in 2017 did not differ significantly between years (P > 0.05). Mummies without adult emergence rate were found to be very high varying between 85 and 100%. This partial parasitic failure observed on A. spiraecola underlines many questions related with different factors (climate, ability of aphids to form winged populations to escape to their enemies, impact of hyperparasitoids). The new field of research is concerning the possible presence of endosymbiont organisms that could give to the aphid a defense reaction against its aggressors.
IDETC 2019-98420 SPACECRAFT FAILURE ANALYSIS FROM THE PERSPECTIVE OF DESIGN DECISION-MAKING

Space mission-related projects are demanding and risky undertakings because of their complexity and cost. Many missions have failed over the years due to anomalies in either the launch vehicle or the spacecraft. Projects of such magnitude with undetected flaws due to ineffective process controls account for huge losses. Such failures continue to occur despite the studies on systems engineering process deficiencies and the state-of-the-art systems engineering practices in place. To further explore the reasons behind majority of the failures, we analyzed the failure data of space missions that happened over the last decade. Based on that information, we studied the launch-related failure events from a design decision-making perspective by employing failure event chain-based framework and identified some dominant cognitive biases that might have impacted the overall system performance leading to unintended catastrophes. The results of the study are presented in this paper.
Effect of Consumer Awareness of Education Material, Source of Information, and Value of Materialism on Behavior as A Smart Adolescent Consumer

This study aims to analyze the effect of consumer awareness about education material, source of information, and value of materialism toward behavior as smart consumer on junior high school student in urban and rural areas of Bogor. Samples in this study are 9 th grade junior high school students as much as 125 students that consisting of 62 students in urban and 63 students in rural areas. The sampling technique is cluster random sampling with the consideration that students have obtained consumer education materials on social sciences and Indonesian language for grade 7 to grade 9. Data were collected by self-administered technique using questionnaires. The results showed that there are differences in consumer awareness about education material, source of information, and objective knowledge of students in urban and rural areas. Gender and source of information affect the behavior as smart consumer on junior high school students.
REST4Mobile: A framework for enhanced usability of REST services on smartphones

Considering end‐user research and proliferation of smartphones and REpresentational State Transfer (REST) interfaces, we envisage that smartphone owners can innovate to compose applications on the small screen. This paper presents the design and evaluation of a REST service development framework (viz, REST4Mobile) with the aim to enhance the usability when consuming on smartphones. Our design process uses the usability factors identified in our previous work as primary constraints for modeling the framework and a corresponding composition tool. Thus, sample REST services are developed with and then without the framework, and usability of composing the services on smartphones is evaluated. Evaluation was conducted by deploying the component REST services, the composition tool, and the resulting composite apps on a local machine. As the task of service composition is conducted directly on the smartphone's screen, the evaluation process is designed to be repeatable on remote servers and on the cloud. Results showed that constraints can be added into the REST architectural style on the basis of the influences of domain specific terms and human cognitive capabilities on the naming and size of the Uniform Resource Identifiers (URIs). In addition, the principles embodying the framework are found to be influential factors in enhancing the usability of REST services on smartphones.