Miracle-dz/UniFAR-FTUs huggingface dataset:
Linear Regression Model Selection Based on Robust Bootstrapping Technique

Problem statement: Bootstrap approach had introduced new advancement in modeling and model evaluation. It was a computer intensive method that can replace theoretical formulation with extensive use of computer. The Ordinary Least Squares (OLS) method often used to estimate the parameters of the regression models in the bootstrap procedure. Unfortunately, many statistics practitioners are not aware of the fact that the OLS method can be adversely affected by the existence of outliers. As an alternative, a robust method was put forward to overcome this problem. The existence of outliers in the original sample may create problem to the classical bootstrapping estimates. There was possibility that the bootstrap samples may contain more outliers than the original dataset, since the bootstrap re-sampling is with replacement. Consequently, the outliers will have an unduly effect on the classical bootstrap mean and standard deviation. Approach: In this study, we proposed to use a robust bootstrapping method which was less sensitive to outliers. In the robust bootstrapping procedure, we proposed to replace the classical bootstrap mean and standard deviation with robust location and robust scale estimates. A number of numerical examples were carried out to assess the performance of the proposed method. Results: The results suggested that the robust bootstrap method was more efficient than the classical bootstrap. Conclusion/Recommendations: In the presence of outliers in the dataset, we recommend using the robust bootstrap procedure as its estimates are more reliable.
Preprint Version Uncertainty-wise Testing of Cyber-Physical Systems

As compared with classical software/system testing, uncertainty-wise testing explicitly addresses known uncertainty about the behavior of a System Under Test (SUT), its operating environment, and interactions between the SUT and its operational environment, across all testing phases, including test design, test generation, test optimization, and test execution, with the aim to mainly achieve the following two goals. First, uncertainty-wise testing aims to ensure that the SUT deals with known uncertainty adequately. Second, uncertainty-wise testing should be also capable of learning new (previously unknown) uncertainties such that the SUT’s implementation can be improved to guard against newly learned uncertainties during its operation. The necessity to integrate uncertainty in testing is becoming imperative because of the emergence of new types of intelligent and communicating software-based systems such as Cyber-Physical Systems (CPSs). Intrinsically, such systems are exposed to uncertainty because of their interactions with highly indeterminate physical environments. In this chapter, we provide our understanding and experience of uncertainty-wise testing from the aspects of uncertainty-wise model-based testing, uncertainty-wise modeling and evolution of test ready models, and uncertainty-wise multi-objective test optimization, in the context of testing CPSs under uncertainty. Furthermore, we present our vision about this new testing paradigm and its plausible future research directions. Keywords— Uncertainty-wise Testing; Cyber-Physical System; Belief Test Ready Model; Model Evolution; Model-Based Testing. —————————— u ——————————
Tree based routing protocol in WSNs: A comparative performance study of the routing protocols DEEC and RPL

Recently, energy optimization in WSNs have strained more and more attention. Enhancing the network lifetime in WSNs is based on minimizing messages exchanged by nodes. Various routing protocols have been proposed to improve the performance of WSNs. Among these protocols, tree-based routing protocols can increase the power efficiency of the network considerably. In this paper, we will evaluate two hierarchical protocols; RPL with the clustering routing protocols DEEC. To evaluate the performance capability of each protocol, comparison results based on the simulation tool Cooja applied in WSN operating system Contiki are presented in this paper.
Efficient Robot Task Learning and Transfer via Informed Search in Movement Parameter Space

Learning complex physical tasks via trial-and-error is still challenging for highdegree-of-freedom robots. The greatest challenge is optimally selecting the next trials to evaluate while improving sample efficiency. We propose a novel learning framework consisting of the task modelling and exploration components. The task model maps the parameter space defining a trial, to the task outcome space. The exploration model enables efficient search in the trial parameter space to generate the subsequent most informative trials, by simultaneously exploiting all the information gained from previous trials and reducing the task model’s overall uncertainty. We validate our framework on a challenging bimanual-robot puckpassing task. Results show that the robot successfully acquires the necessary skills after only 100 trials without any prior information about the task or target positions. Our approach also enables efficient skill transfer to new environments which was validated experimentally.
Assessment of Scapular Position

Assessment of posture is an integral component of the evaluation of patients with neck and shoulder dysfunctions. Protraction of the scapulae has been postulated to produce weakness of the shoulder musculature. Therefore, an accurate method is needed to assess scapular position in order to determine the effect of therapeutic intervention and classify dysfunction. The purpose of this study was to determine if an experienced clinician would accurately determine scapular position. Fifty subjects (age = 26 ±5.7 years, weight = 69.2 ±14.09 kg; height = 173.9 ±13.91 cm) participated in this study. The results revealed the following reliability coefficients: scapular distance (SD) intraclass correlation coefficient (ICC) = . 80, scapular size (SS) ICC = . 96, and normalized scapular abduction (NSA) (SD/SS) ICC = . 34. These data demonstrate that NSA was not reproducible in this study. The authors hypothesize that NSA contains more measurement error because NSA is a ratio value in which both the numerator and denomi.
A Comprehensive Evaluation Approach for Highly Automated Driving

Since the last decade, development efforts by academia and industry for automated driving functions have increased significantly. Also, the European research project AdaptIVe is looking into this topic. Due to the large operation spaces and various complex situations that are covered by these functions, efforts for evaluation increase also significantly. Within AdaptIVe, a comprehensive evaluation approach for automated driving functions ranging from SAE level 2-4 has been developed [1]. The approach splits the evaluation into technical, user-related, in-traffic and impact assessment addressing safety and environmental effects of automated driving. For each evaluation type appropriate test tools and methods are selected e.g. field test for technical assessment, trials on test track and in real traffic for the user-related assessments and simulations for the in-traffic and impact assessment. Next to the assessment type also the characteristics of the function must be considered when deciding for specific test tools. Hence, besides to the level of automation [8] the automated driving functions are classified into continuous and event-based operating functions. Whereas event-based operating functions are only operating for a short period in time (e.g. automated parking), continuous operating functions are, once they are active, operating for longer time periods (e.g. highway automation). Based on the classification the aspects to be evaluated and test methods are selected for all assessment types. The developed methodology has been applied to several automated driving functions developed within AdaptIVe. As an example, for the technical assessment of continuous operating functions it has been assessed whether the driving behavior of the developed functions is similar to human driving behavior and therefore not disturbing human traffic. In the user-related assessment, issues related to driver behavior, understanding of automation, trust, mental workload, resuming control, vigilance, usability and acceptance has been looked at. In this paper the key aspects of the AdaptIVe evaluation methodology for technical, user-related, in-traffic and impact assessment are presented as well as the key results of the application of this methodology on the within AdaptIVe developed automated driving functions. (Less)
Prevalence of Hyperuricemia in Indian Subjects attending Hyperuricemia Screening Programs-A Retrospective Study.

Objectives To determine the prevalence of hyperuricemia (HU) in patients with hypertension (HTN) and type 2 diabetes mellitus (T2DM) in the Indian setting. Methods A retrospective analysis of patients undergoing screening for HU in health clinics across India between April to May 2017 was carried out. Data regarding demographics, history of T2DM and HTN and uric acid levels (easy touch uric acid monitoring system) were recorded during the program. Results Data from 3044 screening programs was analysed. The mean age of the study population was 47.9 years; about two-thirds of the subjects were males. Of the 29391 subjects screened, 25.8% were found to have HU. The proportion of diabetics, hypertensives and diabetic hypertensives who had HU was 33.6%, 35.1%, and 34.4% respectively. A trend towards increased prevalence of HU was seen with increasing age and increased duration of diseases like HTN and diabetes. Conclusion High prevalence of HU was observed in T2DM and HTN and in patients with both co-morbidities. Age-wise analysis revealed an increasing trend of HU with age. Further, the prevalence of HU also increased with increasing duration of T2DM and HTN.
PRODUCTION OF EGG ENRICHED WITH OMEGA-3 FATTY ACIDS IN LAYING HENS

Abstract INTRODUCTION: This experiment was conducted to study the effects of different levels of flaxseed (0, 5, 10 and 15% of diet) and copper (in the form of cupric sulfate pentahydrate, 0 and 250 ppm of diet) on fatty acids and cholesterol in egg yolk of laying hens. methods: A total of 128 White Leghorn layers aged 50 weeks were used in a factorial design and randomly assigned to 8 treatment groups. The experiment lasted 120 days. The birds were fed ad libitum on the experimental diets. Cholesterol concentration and fatty acids in plasma and egg yolk were measured monthly and bimonthly, respectively. Egg yolk cholesterol was extracted using modified Folch procedure and measured using Zak's method. results: The results showed that experimental diets had no effect on plasma cholesterol. The different levels of flax had no significant effect on egg yolk cholesterol but the presence of copper with flax at levels of 5 and 10 percent decreased cholesterol in egg yolk (mg per gram yolk) significantly (P<0.05). The egg cholesterol (mg per egg) in the group treated with 15% flax without copper also decreased significantly (P<0.05). The unsaturated fatty acids of egg yolk increased significantly in all experimental diets (P<0.05). The highest ratio of omega-3 to omega-6 fatty acids was observed in groups treated with 10% and 15% flax diets. DISCUSSION: This experiment showed that feeding flaxseed to laying hens can increase omega-3 fatty acids of egg yolk. Keywords • Laying hen • Egg yolk • Flax • Copper • Plasma • Cholesterol • Fatty acid
Exploiting User Actions for App Recommendations

Mobile Applications (or Apps) are becoming more and more popular in recent years, which has attracted increasing attention on mobile App recommendations. The majority of existing App recommendation algorithms focus on mining App functionality or user usage data for discovering user preferences; while actions taken by a user when he/she decides to download an App or not are ignored. In realistic scenarios, a user will first view the description of the App and then decide if he/she wants to download it or not. The actions such as viewing or downloading provide rich information about users' preferences and tastes for Apps, which have great potentials to advance App recommendations. However, the work on exploring action data for App recommendations is rather limited. Therefore, in this paper we study the novel problem of exploiting user actions for App recommendations. We propose a new framework ActionRank, which simultaneously captures various signals from user actions for App recommendations. Experimental results on real-world datasets demonstrate the effectiveness of the proposed framework.
18 USING HUMAN GENOMICS TO ADVANCE NEUROPSYCHOPHARMACOLOGY

Genomics, the study of genomes, includes gene mapping, sequencing, and investigation of gene functions. This field will advance neuropsychopharmacology in two complementary ways. First, it is hoped that application of genomics technologies to pedigree and population samples of patients with psychiatric disorders will allow the identification of genes contributing to the etiology and pathogenesis of these diseases and provide a rational basis for new drug development. Second, variations in the sequence of known genes whose products are the targets of current psychotropic drugs may influence the likelihood that an individual patient will have a therapeutic response to these drugs or experience a side effect. Identification and functional characterization of these sequence variants in large populations of patients of various ethnicities constitutes the discipline of pharmacogenomics. The scope of psychopharmacogenomics, however, is currently restricted by our limited knowledge of the genes that contribute to psychiatric disorders and the neural pathways altered by psychotropic agents. Fortunately, data and technologies provided by the U.S. Human Genome Project (HGP), including provision of the complete sequence of the human genome, will greatly facilitate identification of such genes (1,2). This chapter describes how technologic advances in genomics will shape the future of psychiatric genetics and psychopharmacogenomics, fields that may establish an objective basis for the restructuring of the nosology, diagnosis, and treatment of psychiatric disorders. The results of genetic studies of particular psychiatric disorders and of responses to specific drugs are considered in other parts of this book.
Aspects of identity: From the inner-outer metaphor to a tetrapartite model of the self

Abstract We review a program of research on identity orientations – the relative importance or value that individuals place on various identity attributes when constructing their self-definitions. We first provide a brief history of the development of our measure of identity orientations – the Aspects of Identity Questionnaire (AIQ) – after which we present our tetrapartite model of the self that distinguishes among individual, relational, public, and collective aspects of identity. We then review previous research on how the four identity orientations uniquely influence cognition, emotion, and behavior, and close by highlighting what we see as interesting and important directions for future research.
Impact of Brachytherapy in the Treatment of Locally Advanced Cervical Cancer: Results from a Single Institution

Introduction: In Morocco, cervical cancer is the second most common cancer, and proximally half of the cases are diagnosed at an advanced stage. The standard treatment approach is concurrent chemoradiation followed by intracavitary brachytherapy (BT) boost to the cervix. Patients and methods: 293 patients diagnosed with cervical cancer and treated with concurrent chemoradiotherapy between January 2011 and December 2011 at our department was retrieved. We analyzed defined prognostic factors influencing outcomes. The aim of our study is to analyze the effect of the use of brachytherapy on treatment outcomes (overall survival and local control) and to report the toxicities for each treatment approach. Results: At 3 years, the use of brachytherapy as boost was found to be a significant factor impacting both OS (P=0.0001)), and LC (P=0.001). Also in the multivariate analysis, brachytherapy was an independent prognosis factor affecting both OS (hazard ratio [HR], 3.29; 95% CI, 1.50-7.21, P=0.03) and LC (hazard ratio [HR], 2.33; 95% CI, 1.30-7.21, P=0.005). Conclusion: At present, brachytherapy is still the standard approach to boost the cervix in patients with locally advanced cervical cancer.
A prospective case series evaluating the safety and efficacy of the Klox BioPhotonic System in venous leg ulcers

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How to not write Virtual Machines for Dynamic Languages

Typical modern dynamic languages have a growing number of implementations. We explore the reasons for this situation, and the limitations it imposes on open source or academic communities that lack the resources to fine-tune and maintain them all. It is sometimes proposed that implementing dynamic languages on top of a standardized general-purpose object-oriented virtual machine (like Java or .NET) would help reduce this burden. We propose a complementary alternative to writing custom virtual machine (VMs) by hand, validated by the PyPy project: flexibly generating VMs from a high-level “specification”, inserting features and low-level details automatically – including good just-in-time compilers tuned to the dynamic language at hand. We believe this to be ultimately a better investment of efforts than the development of more and more advanced general-purpose object oriented VMs. In this paper we compare these two approaches in detail. 1
BEHAVIOURAL CHANGE INTERVENTION

Belief-Desire-Intention (BDI) model is well suited for describing agent’s mental state. The BDI of an agent represents its motivational stance and are the main determinant of agent’s actions. Therefore, explicit understanding of the representation and modelling of such motivational stance plays a central role in designing BDI agent with successful behavioural change interventions. Nevertheless, existing BDI agent models do not represent agent’s behavioural factors explicitly. This leads to a gap between design and implementation where psychological reactance has being identified as the cause of BDI agent behavioural change interventions failure. Hence, this paper presents a generic representation of BDI agent model based on behavioural change and psychological theories. Also, using mathematical analysis the model was evaluated. The objective of the proposed BDI agent model is to bridge the gap between agent design and implementation for successful agent-based interventions. The model will be realized in an agentbased application that motivates children towards oral hygiene. The study explicitly depicts how agent’s behavioural factors interact to enhance behaviour change which will assist agent-based intervention designers to be able to design intervention that will be void of reactance.
Multi-epoch spectroscopy of IY UMa: quiescence, rise, normal outburst and superoutburst

We exploit rare observations covering the time before and during a normal outburst in the deeply eclipsing SUUMa system IYUMa to study the dramatic changes in the accretion flow and emission at the onset of outburst. Through Doppler tomography we study the emission distribution, revealing classic accretion flow behaviour in quiescence, with the stream-disc impact ionizing the nearby accretion disc. We observe a delay of hours to a couple of days between the rise in continuum and the rise in the emission lines at the onset of the outburst. From line profiles and Doppler maps during normal and superoutburst, we conclude that reprocessing of boundary layer (BL) radiation is the dominant emission line mechanism in outburst and that the normal outburst began in the outer disc. The stream-disc impact feature (the orbital hump) in the Halpha line flux light curve disappears before the onset of the normal outburst and may be an observable signal heralding an impending outburst.
Webpage Ranking Analysis of Various Search Engines with Special Focus on Country-Specific Search

In order to attract many visitors to their own website, it is extremely important for website developers that their webpage is one of the best ranked webpages of search engines. As a rule, search engine operators do not disclose their exact ranking algorithm, so that website developers usually have only vague ideas about which measures have particularly positive influences on the webpage ranking. Conversely, we ask the question: ”What are the properties of the best ranked webpages? ” For this purpose, we perform a detailed analysis, in which we compare the properties of the best ranked webpages with the worse ranked webpages. Furthermore, we compare countryspecific differences. TYPE OF PAPER AND
Temporal variability and sources of VOCs in urban areas of Eastern Mediterranean

During the summer of 2012 volatile organic compounds (VOCs) were monitored by Proton Transfer Reaction – Mass Spectrometry (PTR-MS) in urban backgrounds sites, in Athens and Patras, 10 two of the largest cities in Greece. Also during the winter of 2013 PTR-MS measurements were conducted in the center of the city of Athens. Positive matrix factorization (PMF) was applied to the VOC measurements to gain insights about their sources. In summer most of the measured VOCs were due to biogenic and traffic emissions. Isoprene, monoterpenes and several oxygenated VOCs (oVOCs) originated mainly from vegetation either directly 15 or as oxidation products. Isoprene average concentrations in Patras and Athens were 1 ppb and 0.7 ppb respectively while the monoterpene concentrations were 0.3 ppb and 0.9 ppb respectively. Traffic was the main source of aromatic compounds during summer. For Patras and Athens the average concentrations of benzene were 0.1 ppb and 0.2 ppb, of toluene 0.3 ppb and 0.8 ppb and of the xylenes 0.3 ppb and 0.7 ppb respectively. 20 Winter measurements in Athens revealed that biomass burning used for residential heating was a major VOC source contributing both biogenic compounds such as isoprene and the monoterpenes, and aromatic VOCs. Several episodes related to biomass burning were identified and emission ratios (ER) and emission factors (EF) were estimated.