Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges of simulating air showers at ultra-high energy

In this contribution we describe the work on the parallelization of the Monte Carlo code CORSIKA to master the challenges of simulations for development of an Extensive Air Shower initiated by cosmic ray particles at the highest energies of 10 eV. We have implemented workflow system for parallel execution of CORSIKA on distributed computing infrastructures and make preliminary tests simulations for energies up to 10 eV. It allows us to estimate computational needs and challenges for productive simulations at higher energies to escape possible overflows when using parallel job scheduling systems. Introduction One of the problems in simulating Extensive Air Showers (EAS) initiated by cosmic rays at the highest observed energies comes from the huge number of 10 particles which are created within the avalanche by the consecutive interactions with air. Their fate is determined by the flight path between their creation and their interaction or decay, and their nature and energy determines the number, types, energies and directions of the secondary particles generated in the interactions. These stochastic processes are well modelled by Monte Carlo (MC) methods to get correctly not only the mean values (which might be given eventually by analytical approximations) but also the fluctuations and correlations of the measurable shower observables as e.g. lateral distribution of the particles at ground or energy spectra of those particles at different distances to the shower axis. A solution of following this huge number of particles might be the parallelization of the MC code CORSIKA (COsmic Ray SImulations for KAscade) (Heck et al. 1998) to treat independent sub-showers by different cores in parallel. Already in an early stage of the development of the CORSIKA code several possibilities to circumvent the long CPU times which increase nearly linearly with increasing energy of the initiating cosmic particle, were considered (Gils et al. 1993) including various structures of a multi-Transputer computer farm (Gils et al. 1989). Today the availability of multi-core processor systems has revived the parallelization ideas. To master challenges of productive usage of current and future high-end multi-core processors systems an innovative research and support structure, so-called Simulation Laboratories (SimLab), are currently being established at different supercomputing centres in Germany. In particular “SimLab Astro& Elementary Particle Physics” (SimLab A&E Particle) at SCC of KIT is providing support on parallelization of scientific application CORSIKA and porting it into up-to-date distributed and super-computing infrastructures in Europe (Thiara, Poghosyan und Schmitz 2009).
Bounding the Nullities of Random Block Hankel Matrices: An Alternative Approach

Bounds are developed for the probability that various randomly generated block Hankel matrices are rank-deflcient. These bounds are potentially of use to analyze the e‐ciency and reliability of various randomized block Wiedemann and block Lanczos algorithms, that are either currently under development or now in use, when these are applied to solve systems of linear equations and sample from the null space of matrices over small flnite flelds. The bounds that are presented here resemble ones that have previously been obtained using other arguments or that could likely be obtained by straightforward extensions of arguments that have recently been presented. The method used to obtain these bounds in this report is rather difierent and may be of some interest in its own right: It relies only on estimates of the number of irreducible polynomials of a given degree over a flnite fleld and on elementary linear algebra.
Enhancements on Adaptive Congestion Protocol for Wireless Networks

In high Bandwidth Delay Product (BDP) networks, Adaptive congestion Control Protocol (ACP) is emerging as one potential solution for overcoming limitations inherent to the current TCP algorithm, characterized by unstable throughput, high queuing delay, RTT-limited fairness. However, its performance in wireless network is deeply not investigated. In this paper, we address the challenges when applying ACP to wireless networks, and extend ACP, called iACP to enhance its performance in wireless networks. ns2 simulation results demonstrate that iACP can fairly and efficiently allocate bandwidth in homogenous and heterogeneous network.
Vapor Hydrofluoric Acid Sacrificial Release Technique for Micro Electro Mechanical Systems Using Labware

We have developed a novel technique of sacrificial layer etching for micro electro mechanical systems (MEMS). Our technique uses vapor of hydrofluoric acid (HF) to etch sacrificial silicon oxide and to make freestanding silicon microstructures. The advantages of this technique are: (1) no subsequent water rinse is needed, (2) freestanding silicon microstructures can be successfully released without sticking to the substrate, (3) equipment for our vapor phase HF etching simply consists of Teflon beakers only. Conditions for the technique have been optimized by estimating etching rate with test patterns made of silicon-on-insulator (SOI) wafers and by observing water droplets condensation on the sample surface with thermally oxidized silicon chips. By this technique we have successfully obtained freestanding microstructures of SOI wafers. Microcantilevers of as long as 5000 µm (a 5-µm-wide, 10-µm-thick, and 5000-µm-long cantilever over a 0.6-µm-gap) have been successfully released without adhering to the base substrate or contacting the neighboring cantilevers. We have also fabricated and actuated electrostatic comb-drive actuators of 60 and 200 comb pairs to demonstrate high processing yield of our nonstick releasing technique.
Advances in Wearable Sensing Technologies and Their Impact for Personalized and Preventive Medicine

Recent advances in miniaturized electronics, as well as mobile access to computational power, are fostering a rapid growth of wearable technologies. In particular, the application of such wearable technologies to health care enables to access more information from the patient than standard episodically testing conducted in health provider centres. Clinical, behavioural and self-monitored data collected by wearable devices provide a means for improving the early-stage detection and management of diseases as well as reducing the overall costs over more invasive standard diagnostics approaches. In this chapter, we will discuss some of the ongoing key innovations in materials science and micro/nano-fabrication technologies that are setting the basis for future personalized and preventive medicine devices and approaches. The design of wire- and power-less ultra-thin sensors fabricated on wearable biocompatible materials that can be placed in direct contact with the body tissues such as the skin will be reviewed, focusing on emerging solutions and bottlenecks. The application of nanotechnology for the fabrication of sophisticated minia- turized sensors will be presented. Exemplary sensor designs for the non-invasive measurement of ultra-low concentrations of important biomarkers will be discussed as case studies for the application of these emerging technologies.
Customers’ Opinion Mining from Extensive Amount of Textual Reviews in Relation to Induced Knowledge Growth

Customers of various services are often invited to type a summarizing review via an Internet portal. Such reviews, written in natural languages, are typically unstructured, giving also a numeric evaluation within the scale “good” and “bad. ” The more reviews, the better feedback can be acquired for improving the service. However, after accumulating massive data, the non-linearly growing processing complexity may exceed the computational abilities to analyze the text contents. Decision tree inducers like c5 can reveal understandable knowledge from data but they need the data as a whole. This article describes an application of windowing, which is a technique for generating dataset subsamples that provide enough information for an inducer to train a classifier and get results similar to those achieved by training a model from the entire dataset. The windowing results, significantly reducing the complexity of the learning problem, are demonstrated using hundreds of thousands reviews written in English by hotel-service customers. A user obtains knowledge represented by significant words. The results show classification accuracy errors, training and testing time, tree sizes, and words relevant for the review meaning in dependence on the training subsample size. Finally, a method of suitable training-set size estimation is suggested.
Effect of Agricultural Extension Program on Smallholders' Farm Productivity: Evidence from Three Peasant Associations in the Highlands of Ethiopia

This study evaluates the effect of agricultural extension program participation on farm productivity taking three case study kebeles (peasant associations) in Ethiopia. A total of 1112 plot-level data collected from 300 selected farm households, comprising of extension participants and non-participants, were used in the study. The study begins the estimation with simple Ordinary Least Square (OLS) method. To deal with the potential bias due to the existence of observed and unobserved characteristics, we employed Heckman Treatment Effect Model (HTEM) and Propensity Score Matching (PSM). The OLS result shows that extension participation increases farm productivity by about 6%. However, both HTEM and PSM clearly reveal the presence of selection bias in extension program participation which leads to underestimation of the OLS estimates. The participation could have increased farm productivity by up to 20% had it not been to the serious selection bias related to non-farming factors such as involvement in kebele administration, and wealth status of the participants observed during program placement. Our PSM analysis also verifies the positive effect of extension program participation on farm productivity. In conclusion, the extension program has a positive effect on farm productivity in the study area. However, its effect with its current structure and input could have tripled had there been no bias related to extension program participation. This result provides a valuable policy insight in which improving access to diversified and quality agricultural inputs are critically necessary for the participants on top of expanding the program to less resourceful farmers by avoiding any entry barriers in the future.
Agricultural Growth and Regional Disparity in India: A Convergence Analysis

The deceleration in growth trends in agricultural output and yield rate is a matter of great concern in recent years in India. This study makes an attempt to examine the growth performances of agricultural production and productivity of major States of India and the nature and extent of disparity in the performances of agriculture. The growth performances have been analyzed considering three distinct phases of agricultural development in India viz the first phase of green revolution 1970-71 to 1979-80, second phase of green revolution 1980-81 to 1990-91, and the period after economic reform 1991-92 to 2007-08). The agricultural infrastructural index, constructed using Principle Component Analysis, reveals the prevalence of a wide inter-state variation in agricultural infrastructure in India. Moreover, using Generalized Method of Moments (GMM) under the panel data framework, the study attempts to examine the trends of convergence/divergence of per capita value of agricultural output over the period 1970-71 to 2007-08. The results of conditional convergence establish the argument that variations in the provision of agricultural infrastructure and natural factor like rainfall play the divergent role in accruing benefits from agriculture in India. The skewed distribution of public and private investment in favour of agriculturally developed states has been found to be responsible for enhancing the disparity in agricultural infrastructure and thus, to the per capita net state domestic product across states in India.
Constructing Identities - Developing Skills: Cases of Workers with Poor Literacy Skills

The Vygotskian concept of a Zone of Proximal Development (ZPD) has been explored extensively in school education settings as a means of determining cognitive change. Evidenced in settings characterised by social activity ZPDs are present in the cognitive process that occur when humans interact in and with their natural or man made environments. While most research around ZPDs concerns classrooms, particularly in the early years, this paper reports on a study of nine workers who self-report literacy difficulties. The study investigated whether the artefacts of as well as the human interactions that take place in the workplace merged in ZPDs to enhance the cognitive process. Results demonstrate a quite particular set of human and man made factors that result in new skills in solving novel problems in the workplace. Further the study illustrates how cognitive skills develop into adulthood and result in enhanced concepts of identity. Implicit in this process is recognition of a range of multiple literacies. The study concludes that Vygotsky’s notion deserves reconceptualisation for learning settings that Vygotsky did not consider.
Profiling four brackish-water harbours : zoobenthic composition and invasion status

Many studies worldwide have emphasized the need to map the potential of commercial ports to function as receiver and donor areas for nonindigenous species (NIS). In this study, the macroinvertebrate composition of hard and soft sea bottoms, hydrographical conditions, and traffic connections of four Finnish coastal harbours (Naantali, Koverhar, Porvoo, Hamina) were investigated and compared with 'natural' reference areas lacking anthropogenic constructions. The harbours hosted macroinvertebrate communities fairly similar to those found in adjacent reference areas, but sediment community diversity was slightly higher in harbour basins relative to in surrounding areas. A total of eight NIS were registered in the study. With regard to hydrography, NIS that tolerate low salinities, low temperatures and eutrophic conditions are most likely to survive local conditions and hence pose a potential risk for larger areas of the Baltic Sea. A ship traffic analysis revealed that the most important donor and recipient areas of ballast water to and from the study harbours are coastal harbours of other parts of the Baltic Sea and of the North Sea. Some suggestions are made for future harbour surveys along the Finnish coast.
An adsorption theory of heterogeneous nucleation of water vapour on nanoparticles

Abstract. Heterogeneous nucleation of water vapour on insoluble nuclei is a phenomenon that can induce atmospheric water and ice cloud formation. However, modelling of the phenomenon is hampered by the fact that the predictive capability of the classical heterogeneous nucleation theory is rather poor. A reliable theoretical description of the influence of different types of water-insoluble nuclei in triggering the water condensation or ice deposition would help to decrease uncertainty in large-scale model simulations. In this paper we extend a recently formulated adsorption theory of heterogeneous nucleation to be applicable to highly curved surfaces, and test the theory against laboratory data for water vapour nucleation on silica, titanium dioxide and silver oxide nanoparticles. We show that unlike the classical heterogeneous nucleation theory, the new theory is able to quantitatively predict the experimental results.
Strong-Coupling Expansion for the Hubbard Model

A strong-coupling expansion for models of correlated electrons in any dimension is presented. The method is applied to the Hubbard model in $d$ dimensions and compared with numerical results in $d\phantom{\rule{0ex}{0ex}}=\phantom{\rule{0ex}{0ex}}1$. Third order expansion of the Green's function suffices to exhibit both the Mott metal-insulator transition and a low-temperature regime where antiferromagnetic correlations are strong. It is predicted that some of the weak photoemission signals observed in one-dimensional systems such as ${\mathrm{SrCuO}}_{2}$ should become stronger as temperature increases away from the spin-charge separated state.
Modelling of Microalgae Growth and Oil Production by Using Sewage and Carbon Dioxide for Biodiesel

With the depletion of the world fossil oil reserves, microalgae biodiesel might become one of the economic, renewable and carbon-neutral sources of transportation biofuels. This study investigates marine microalgae growth and biodiesel production by cultivating highly productive oleaginous microalgae at large scale using sewage as nutrient supply and waster CO2 as carbon source. Five strains of marine microalgae will be screened in the laboratory for their biomass productivity and lipid content. The best strain will be optimised for the cultivation parameter, including initial pH value, dissolved carbon dioxide concentration, proportion of sewage mixture and illumination intensity. The result showed Chlorella and Nannochloropsis Local have the better biomass production.
Testing for unobserved heterogeneous treatment effects in a nonseparable model with endogenous selection

Unobserved heterogeneous treatment effects have been emphasized in the policy evaluation literature. This paper proposes a nonparametric test for unobserved heterogeneous treatment effects in a general framework, allowing for self-selection to the treatment. The proposed modified Kolmogorov-Smirnov-type test is consistent and simple to implement. Monte Carlo simulations show that our test performs well in finite samples. For illustration, we apply our test to study heterogeneous treatment effects of the Job Training Partnership Act on earnings and the impacts of fertility on family income.
Estrogen Fluctuations in the Female Menstrual Cycle

Name: Jessie Thiessen Graduation Date: May 2017 Title: Estrogen Fluctuations in the Female Menstrual Cycle First Reader: Dr. Becky Dawson Second Reader: Dr. Chris Lundberg The female menstrual cycle (Figure 1) is a series of changes that women go through in order to prepare for reproduction (Sharma et al., 2016). Hormones present during the menstrual cycle can fluctuate depending on a number of mental and physical health factors (Manikandan et al., 2016). Estrogen is produced in women and most present during ovulation in the menstrual cycle (Stijak et al. 2015). Estradiol is responsible for female sex characteristics and sexual functioning (Otag et al., 2016). The effect of exercise on estrogen levels in the female menstrual cycle is examined in this experiment. Two groups of human females participated – ten active females and eight females that are not active on a regular basis. Saliva samples were collected on day one and day fourteen of each participant’s menstrual cycle. On day one of their menstrual cycle, participants completed a survey to determine the demographics of each participant. An estradiol enzyme-linked immunosorbent assay (ELISA) was performed on each sample to measure the amount of estrogen in each sample. There was no significant difference between active and non-active participants on day one of sample collection (F(1) = 0.1553, P = 0.6988) (Figure 3). There was no significant difference between active and non-active participants on day fourteen of sample collection (F(1) = 0.000, P = 0.9980) (Figure 4). There was no significant difference between day one and day fourteen of the female menstrual cycle (Figure 5). The purpose of this experiment was to determine the influence of physical activity on estrogen levels in women. TABLE OF CONTENTS Acknowledgements.
A Novel Term Selection Approach in sLDA for Imbalanced Text Categorization

The supervised Latent Dirichlet Allocation (sLDA) is a probabilistic topic model of labelled documents, which is better than unsupervised LDA for text categorization. But sLDA experiments were based upon this default assumtion that the corpus is balanced, that is, the samples of each class are approximately equal, and chose a vocabulary by tf-idf. While the corpus is imbalanced, tf-idf tends to choose terms from the majority classes and ignore terms of the minority ones. Thus the performance of text classifier will be degraded severely. Therefore this paper proposed a new term selection approach which can fairly choose more discriminative terms from every category. Experimental results show that using this new approach in sLDA for imbalanced text categorization can greatly impove the recall and precision of the minority classes, and it is superior to tf-idf.
Teaching and learning in further education: The Ofsted factor

Abstract The further education (FE) sector in the UK, or post-compulsory education as it is often referred to, has undergone some radical changes in recent years. Historically, FE is synonymous with vocational education and training, providing communities with courses that tended to be in practical, non-academic subjects. Many FE lecturers came from industries such as construction and engineering and were vital in providing the subject knowledge needed by colleges to enable them to offer a wide provision of courses. However, FE had not undergone the regime of teacher qualifications, regulation and inspection to the extent experienced by schools. In 2001, the New Labour government began a series of reforms that would overhaul post-compulsory education with the objective of making the sector more effective, and thereby meeting the wider objective of creating a more productive workforce. One of the many reforms was to introduce a system of inspection by placing FE into Ofsted’s remit. The new reform prompted FE colleges, for the first time, to implement their own institutional policies of observing teaching and learning (OTL) in order to prepare for impending inspection by Ofsted. This article examines the implementation of the policy of OTL, with a focus on one college of FE, and scrutinises its effects on the sector.
Contagion and the Role of Market Development: the Case of the Malaysian Futures Market during the East Asian Crisis of 1997

In looking to explain the possible transmission and causal flows in volatility between financial markets during an economic crisis and the impact of possible contagion, we examine the specific circumstances surrounding the role of the development of futures index trading in Malaysia in relation to the East Asian (or Asian) crisis of the late 1990's. Specifically, our main contribution is to assess whether an undeveloped and subsequently developing futures market had the 'efficiency capacity' to transmit fair prices and, failing that, whether price contagion was spread via futures index trading.
Impact of quality-led design on real estate value: a spatiotemporal analysis of city centre apartments

Abstract This paper estimates the impact of quality design attributes on real estate value through empirical investigation of the owner-occupied multifamily residential sector. The methodological design is based on spatiotemporal modelling using a unique data-set of 424 Belfast City Centre apartments sold during the period 2000–2008. The key findings indicate that urban scale aspects of quality such as connectivity and vitality associated with building density add to real estate value. At the building level, quality features highly valued by home buyers are namely appropriateness of material quality, fenestration and massing to the surroundings. These key criteria are considered to have a significant visual perception compared to more complex concepts such as identity, material choice and overall condition. The contribution to knowledge involves extending the hedonic model to incorporate a wider selection of design quality variables; and improving estimation through the use of spatiotemporal modelling.