Miracle-dz/UniFAR-FTUs huggingface dataset:
Coupled regularization with multiple data discrepancies

We consider a class of regularization methods for inverse problems where a coupled regularization is employed for the simultaneous reconstruction of data from multiple sources. Applications for such a setting can be found in multi-spectral or multi-modality inverse problems, but also in inverse problems with dynamic data. We consider this setting in a rather general framework and derive stability and convergence results, including convergence rates. In particular, we show how parameter choice strategies adapted to the interplay of different data channels allow to improve upon convergence rates that would be obtained by treating all channels equally. Motivated by concrete applications, our results are obtained under rather general assumptions that allow to include the Kullback–Leibler divergence as data discrepancy term. To simplify their application to concrete settings, we further elaborate several practically relevant special cases in detail. To complement the analytical results, we also provide an algorithmic framework and source code that allows to solve a class of jointly regularized inverse problems with any number of data discrepancies. As concrete applications, we show numerical results for multi-contrast MR and joint MR-PET reconstruction.
Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results

Causal discovery methods aim to recover the causal process that generated purely observational data. Despite its successes on a number of real problems, the presence of measurement error in the observed data can produce serious mistakes in the output of various causal discovery methods. Given the ubiquity of measurement error caused by instruments or proxies used in the measuring process, this problem is one of the main obstacles to reliable causal discovery. It is still unknown to what extent the causal structure of relevant variables can be identified in principle. This study aims to take a step towards filling that void. We assume that the underlining process or the measurement-error free variables follows a linear, non-Guassian causal model, and show that the so-called ordered group decomposition of the causal model, which contains major causal information, is identifiable. The causal structure identifiability is further improved with different types of sparsity constraints on the causal structure. Finally, we give rather mild conditions under which the whole causal structure is fully identifiable.
Exploring the co-evolution of air transport aviation and corporate networks

In this paper we aim to contribute to the literature on the empirical parallels between urban hierarchies and the transport networks supporting and/or reflecting these hierarchies. We adopt a stochastic actor-based modeling framework to analyze the co-evolution of the world city hierarchy and global air passenger networks between 2000 and 2010/2011. The data are drawn from an inventory of the location strategies of globalized service firms across world cities and the International Civil Aviation Organization (ICAO). Major findings include (1) exogenous effects, such as the impact of economic development and regionality; (2) endogenous micro-level effects producing macro-level patterns, such as preferential attachment processes; and (3) the two-way impact of both networks. (i.e., cities that are well connected in the aviation network tend to attract more major offices of globalized service firms, while the co-presence of major offices of globalized service firms in cities in turn stimulates the development of aviation connections between them).
High-Performance Low-Cost Electric Motor for Electric Vehicles Using Ferrite

Permanent magnet motors with rare earth magnets are amongst the best candidates for high performance applications such as automotive. However, due to their cost and risks relating to security of supply, alternative solutions such as ferrite magnets have recently become popular. In this paper the two major design challenges of using ferrite magnets for a high torque density and high speed application, namely their low remanent flux density and low coercivity, are addressed. It is shown that a spoke type design utilizing a distributed winding may overcome the torque density challenge due to a simultaneous flux concentration and reluctance torque possibility. Furthermore, the demagnetization challenge can be overcome through careful optimization of the rotor structure, with the inclusion of non-magnetic voids on the top and bottom of the magnets. To meet the challenges of the high speed operation an extensive rotor structural analysis has been undertaken, during which electro-magnetics as well as manufacturing tolerances are taken into account. The electromagnetic studies are validated through testing of a prototype, custom built for static torque and demagnetization evaluation. The disclosed motor design surpasses the state of the art performance and cost, merging the theories into a multi-disciplinary product.
High-dimensional neural network potentials for metal surfaces: A prototype study for copper

The atomic environments at metal surfaces differ strongly from the bulk, and, in particular, in case of reconstructions or imperfections at ``real surfaces,'' very complicated atomic configurations can be present. This structural complexity poses a significant challenge for the development of accurate interatomic potentials suitable for large-scale molecular dynamics simulations. In recent years, artificial neural networks (NN) have become a promising new method for the construction of potential-energy surfaces for difficult systems. In the present work, we explore the applicability of such high-dimensional NN potentials to metal surfaces using copper as a benchmark system. A detailed analysis of the properties of bulk copper and of a wide range of surface structures shows that NN potentials can provide results of almost density functional theory (DFT) quality at a small fraction of the computational costs.
Iron and humic‐type fluorescent dissolved organic matter in the Chukchi Sea and Canada Basin of the western Arctic Ocean

[1] The concentrations of dissolved Fe ([D-Fe]), total dissolvable Fe ([T-Fe]), humic-type fluorescence intensity (humic F intensity) as humic-type fluorescent dissolved organic matter, and nutrients were vertically determined in the shelf, slope, and basin regions (Chukchi Sea and Canada Basin) of the western Arctic Ocean during 1–27 September 2008. In all stations, the remarkably high [D-Fe] and humic F intensity were found at depths between 25 and 200 m with the subsurface maxima of [D-Fe] (1.0–3.2 nM) and humic F intensity (4–5 quinine sulfate units) in the upper halocline layer (upper HL), being associated with a prominent nutrient maximum. The high [D-Fe] and humic F intensity within the upper HL are probably attributed to the Fe(III) complexation with natural organic ligands, such as marine dissolved humic substances, resulting from main processes of the brine rejection during sea ice formation and interactions with sediments on the shelves. However, subsurface maxima (10–50 nM) of [T-Fe] were found in the lower halocline layer, beneath the upper HL, of all slope and basin regions and are mainly attributed to the resuspension of sedimentary particles in the shelf region. The finding of subsurface iron maxima in the halocline water of all regions may be the first confirmation for the lateral iron transport into the halocline layer from the shelves to the Arctic Basin.
Primary Multidrug-Resistant Mycobacterium Tuberculosis (P-MDRTB) in Gorgan, Iran

Background: Resistance to anti-tuberculosis (TB) drugs is a global problem. Previous studies showed that the prevalence of primary MDR-TB is higher and has been increasing. The purpose of this study was to determine the primary drug resistance in strains isolated from patients with smear-positive of the new cases to anti-TB drugs. Methods: In this cross-sectional study, 266 smear positive pulmonary TB Iranian patients were enrolled during the April 2011 and March 2012. Drug Susceptibility Testing (DST) of M. tuberculosis isolates to the first-line drugs, isoniazid, rifampicin, ethambutol, and streptomycin, were performed by the proportion method using conventional Lowenstein-Jensen (L-J) medium. Results: The average age was 48.4 ± 21.3 years, and 56.5 percent were male. In this study, out of 266 pulmonary TB suspects studied, susceptibility testing was performed for 189 isolates. Resistance to at least one drug was present in 11.1% (21/189) of cases. Resistance among newly diagnosed patients was most common for streptomycin, and MDR prevalence rates (resistant to ISONIAZID and RIFAMPIN) among these patients were 2.1%. Conclusions: Our finding suggests that the incidence of MDR tuberculosis in high TB burden settings stresses the need for drug susceptibility testing to be done for every patient who is culture positive for Mycobacterium tuberculosis.
A Discrete-Time Queue with Preferred Customers and Partial Buffer Sharing

We analyze a discrete-time Geo/Geo/1 queueing system with preferred customers and partial buffer sharing. In this model, customers arrive according to geometrical arrival processes with probability . If an arriving customer finds the server idle, he begins instantly his services. Otherwise, if the server is busy at the arrival epoch, the arrival either interrupts the customer being served to commence his own service with probability (the customer is called the preferred customer) or joins the waiting line at the back of the queue with probability (the customer is called the normal customer) if permitted. The interrupted customer joins the waiting line at the head of the queue. If the total number of customers in the system is equal to or more than threshold , the normal customer will be ignored to enter into the system. But this restriction is not suitable for the preferred customers; that is, this system never loses preferred customers. A necessary and sufficient condition for the system to be stable is investigated and the stationary distribution of the queue length of the system is also obtained. Further, we develop a novel method to solve the probability generating function of the busy period of the system. The distribution of sojourn time of a customer in the server and the other indexes are acquired as well.
Fractal Analysis of Cardiovascular Signals Empowering the Bioengineering Knowledge

The cardiovascular system is composed of a complex network of vessels, where highly uniform hierarchical branching structures are regulated by the anatomy and local flow requirements. Arteries bifurcate many times before they become capillaries where the scaling factor of vessel length, diameter and angle between two children branches is established at each level of recurrence. This behaviour can be easily described using a fractal scaling principle. Moreover, it was observed that the basic pattern of blood dis tribution is also fractal, imposed both by the anatomy of the vascular tree and the local regulation of vascular tone. In this chapter, arterial physiology was analysed, where waveform complexity of arterial pressure time series was related to arterial stiffness changes, pulse pressure variations and the presence wave reflection. Fractal dimension was used as a nonlinear measure, giving place to a ‘holistic approach of fractal dimension variations throughout the arterial network’, both in health and disease.
Diagnóstico de faltas em um sistema de distribuição subterrâneo utilizando redes neurais artificiais

 The process of localization and classification of faults in underground distribution systems is of extreme importance and complex in some cases. This paper proposes a methodology that indicates the involved area in a situation of short-circuit, and, thereafter, to perform the classification of the fault type. The whole process is based on the use of Artificial Neural Networks. An advantage of this method is that only the root mean square values of the voltages recorded by meters allocated optimally on the distribution system are used. The results observed to date are promising and show a high efficiency of the neural networks used. Keywords Underground distribution systems, fault diagnosis, artificial neural networks, power quality. Resumo O processo de localização e classificação de faltas em sistemas de distribuição subterrâneos é de extrema importância, podendo ser complexo em alguns casos. Neste trabalho, propõe-se uma metodologia para determinar a área que envolve uma situação de curto-circuito, e, a partir desta, executar a classificação quanto ao tipo da falta. Todo o processo é realizado baseando-se na utilização de redes neurais artificiais. Uma vantagem deste método é a utilização somente dos valores eficazes das tensões registradas por medidores alocados de forma otimizada no sistema de distribuição. Os resultados observados até o momento são promissores e apontam uma elevada eficiência por parte das redes neurais utilizadas. Palavras-chave Sistema de distribuição subterrâneo, diagnóstico de faltas, redes neurais artificiais, qualidade da energia elétrica.
Effects of Dietary Chrysin Supplementation on Blood Pressure and Oxidative Status of Rats Fed a High-Fat High-Sucrose Diet

*To whom correspondence should be addressed. E-mail: Yamamoto@tokaigakuen-u.ac. jp Introduction The pathogenesis of a wide range of lifestyle diseases such as hypertension and cardiovascular disease is not fully understood. However, the role of oxidative stress on the genesis and maintenance of these diseases has been revealed in experiments involving administration of several types of antioxidants, with a consequent lowering of the risk of these diseases (Rodríguez et al., 2002; Vasdev et al., 2001; Chen et al., 2001; Schnackenberg and Wilcox, 1999). Oxidative stress initiated by reactive oxygen species (ROS) might be a factor in these pathological conditions via oxidation of biological macromolecules such as lipids, protein, and DNA. Thus, there is growing interest in the many antioxidative components in foods for the prevention of ROS-induced oxidative damage. Flavonoids are widely distributed in many kinds of plant food sources. The beneficial effects of flavonoids on human health have been widely studied, and antioxidative activity was proposed as one of the most important causes of these effects (Duarte et al., 1993; Duarte et al., 2001; Yamamoto and Oue, 2006; Gryglewski et al., 1987; Yu et al., 2006; Villar et al., 2002). Quercetin is the most abundant flavonol type of flavonoid, and a wide range of biological actions including vasodilation, antihypertensive, and antithrombotic effects have been reported (Duarte et al., 1993; Duarte et al., 2001; Yamamoto and Oue, 2006). Chrysin is a flavone-type flavonoid, and is present in foods like honey and propolis, and in many kinds of fruits and vegetables at low concentrations. Additionally, chrysin is commercially available as an androgen-boosting supplement (Kao et al., 1998). Previous experiments have suggested that chrysin possesses in vitro antioxidative and free radical scavenging activities (Rackova et al., Original paper
Multi-Class Learning: From Theory to Algorithm

In this paper, we study the generalization performance of multi-class classification and obtain a shaper data-dependent generalization error bound with fast convergence rate, substantially improving the state-of-art bounds in the existing data-dependent generalization analysis. The theoretical analysis motivates us to devise two effective multi-class kernel learning algorithms with statistical guarantees. Experimental results show that our proposed methods can significantly outperform the existing multi-class classification methods.
Estimating the Profit Cost Functions, Economic and Technical Efficiencies of Corn Production in Babylon Province in Iraq

The study aimed to estimate the profit and cost functions as well as the economic, price and cost efficiencies of local and hybrid varieties of corn. A random sample of 80 corn farms in Babylon province were selected during the agricultural season 2013. From efficiency scales of profit functions, it was shown that the production size had the greatest impact on the profit of both local and hybrid seeds compared with the other price variables and average production costs. According to the cost functions, the optimal cost-minimizing production sizes were 40.7 ton and 47.77 ton for local and hybrid seeds respectively; while the technical efficiency, economic efficiency, price efficiency and cost efficiency for these seeds were respectively 20.996% and 49.88% ; 20.996% and 49.88% ; 22.34% and 38.74; and 0.49 and 0.59. From these results it can be concluded that employed economic resources in the production process were not optimally exploited which resulted in a reduction in technical efficiencies for both varieties of seeds. The study recommended to follow production policy aiming to increase the economic efficiency and achieve the optimal usage of available resources
Effect of Penicillium Extractsa on Germination Vigor in Subsequent Seedling Growth of Tomato (Solanum Lycopersicum L.)

Abstract Penicillium spp. are well known to produce a variety of beneficial metabolites for plant growth and survival, as well as defend their hosts from attack of certain pathogens. In this study, effects of culture filtrate of different Penicillium spp. were tested on tomato seeds. On the whole, presoaking of seeds in filtrates of the nine Penicillium isolates tested, significantly increased seed germination when compared with the control seeds. Cultural extracts of P. expensum and P. billi were highly effective in growth promotion up to 90%. It was also observed that P. implicatum and P. oxlalicam significantly enhanced the root growth in tomato seedling as compare to other species. In case of shoot length, P. verrucosum (3.38), P. granulatum (2.81) and P. implicatum (2.62) were effective. However P. implicatum was quite promising to increase shoot and root length in tomato seedlings. Where as P. simplicissimium and P. citrinum were leas effective on seedling growth. The plant growth promoting ability of Penicillium strains may help in growth permotion in other plants and crops. Penicillium spp. are already known for producing mycotoxin and enzymes. Plant growth promoting ability of Penicillium spp will open new aspects of research and investigations. The role of Penicil-lium spp. in tomato plant growth requires further exploration.
Exploring reticence in research methods: The experience of studying psychological research methods in higher education

As a fundamental element of any psychology degree, the teaching and learning of research methods is repeatedly brought into sharp focus, and it is often regarded as a real challenge by undergraduate students. The reasons for this are complex, but frequently attributed to an aversion of maths. To gain a more detailed understanding of students’ relationship with psychological research methods, the current study used small, semi–structured focus groups to explore the experience of undergraduate students at the end of their first year of study. Following a detailed thematic analysis of the interview texts, five overarching themes emerged: prior knowledge of research methods; personal engagement with the module; enabling access to learning; supportive learning content; and personal development. Insights gained from the findings are discussed, including possible helpful interventions, but overall the results suggest a more positive outlook than may have been expected.
Towards an ecosystem approach to fisheries management (EAFM) when trawl surveys provide the main source of information

Ideas and considerations are put forward for managing fisheries and marine populations using primarily trawl surveys to supply biological and spatial indicators of the state of stocks, and to permit catch per unit effort (CPUE)-based assessments. Trawl surveys seldom allow absolute estimates of fish population sizes but, if appropriately located, timed, and designed, can provide a broad range of information about catchable fish species and the ecosystem that supports them. This information may be more conducive to sustainable management of fisheries than the traditional focus on the abundances of selected stocks. The paper first briefly proposes how survey-based methods might supplement existing fishery-dependent stock assessments, as would be necessary during a transition phase to a more ecosystem-orientated system of management. Full survey-based management is then considered in relation to management objectives, the selection of indicators, survey design, reference periods, levels and directions, statistical aspects, CPUE-based assessments, and management responses to good and bad signals from the ecosystem. We argue that existing fishery-dependent stock assessments cannot be claimed to produce absolute estimates of stock abundance and fishing mortality because natural mortality (M) is seldom known accurately and, therefore, that they should not be presumed superior to the relative information from surveys, and an agreeable form of adaptive management.
A Distributed Model of Four-Port MonolithicTransformer

This paper deals with modeling of a monolithic spiral transformer. The transformer is designed and fabricated as a symmetrical octagonal spiral structure using two-metal layer process on GaAs substrate for input balun applications of 2 GHz and 5 GHz push-pull power amplifiers. A distributed model of the transformer is developed to fit in wide frequency range with four ports. The model includes the skin effect which describes increase in series resistance with frequency. Six different sets of twoport s-parameters are measured to obtain full characteristics of the four-port transformer while the other two ports are shorted to ground. The model is validated with measurement results in 100 MHz to 6 GHz.
Internal parasites prevalent in California's beef cattle

Sixty percent of cattle not dewormed within 4 months of sampling were shedding parasite eggs or larva. The prevalence of shedding varied greatly for different types of internal parasites. Prevalence of shedding for major Strongylate nematodes was 54%; thread-necked intestinal nematodes, 6%; lungworms, 0.8%; coccidia, 18.1%; and tapeworms, 2.1%. Anthelmintic (deworming) treatments lowered prevalence compared to untreated cattle, but the major Strongylate nematodes and coccidia were still sufficiently prevalent that the resulting pasture contamination would restrict the potential success of control programs.