Miracle-dz/UniFAR-FTUs huggingface dataset:
1 Extending the Coverage Area of Regional Ionosphere Maps Using a Support Vector Machine Algorithm

The coverage of regional ionosphere maps is determined by the distribution of ground monitoring stations, e.g. GNSS receivers. Since ionospheric delay has a high spatial correlation, ionosphere map coverage can be extended using spatial extrapolation methods. This paper proposes a support vector machine (SVM) to extrapolate the ionospheric map data with solar and geomagnetic parameters. One year of IGS ionospheric delay map data over South Korea is used to train the SVM algorithm. Subsequently, one month of ionospheric delay 5 data outside the input data region is estimated. In addition to solar and geomagnetic environmental parameters, the ionospheric delay data from the inner data region are used to estimate the ionospheric delay data for the outside region. The accuracy evaluation is performed at three levels of range – 5 ̊, 10 ̊, and 15 ̊ outside the inner data regions. The estimation errors are 0.33 TECU for the 5 ̊ region and 1.95 TECU for the 15 ̊ region. These values are substantially lower than the GPS Klobuchar model error values. Comparison with another machine 10 learning extrapolation method, the neural network, shows a substantial improvement of up to 26.7%.
Creating model systems for catalysis with mass-selected nanoparticles: Characterization and properties

In our current study, we investigated well-characterized model systems of mass-selected NiFe nanoparticles for the oxygen evolution reaction in alkaline media. We tested the catalysts electrochemically in 1 M KOH and our results show that the particles have one of the highest turnover frequency in alkaline media among the non-noble oxygen evolution catalysts reported. During a 1000 h chronoamperometric measurement at 1.6 V vs RHE the particles showed no degradation of performance. We also investigated the effect of particle proximity on the activity and found that the particles are less active the closer they are to each other. Furthermore, we explored the changes induced by reaction conditions in the crystal structure of the particles with XRD and HRTEM and the changes in the binding state of Ni and Fe with XPS. *: These authors contributed equally to the manuscript Sintering of mass-selected Au and AuTi clusters on SiO2: A STEM and computational study Yubiao Niu, Philomena Schlexer, Bela Sebok, Ib Chorkendorff, Gianfranco Pacchioni, Richard E Palmer : Nanoscale Physics Research Laboratory, School of Physics and Astronomy, University of Birmingham, B15 2TT, Birmingham, United Kingdom : Dipartimento di Scienza dei Materiali, Università di Milano-Bicocca, 20125 Milano, Italy : Department of Physics, SurfCat, Technical University of Denmark, DK-2800, Kgs. Lyngby,
Effect of Evolvulus Alsinoides L. Ethanolic Extract and Its Fraction In Experimentally Induced Hyperlipidemia In Rats

Summary The present study was undertaken to explore the antihyperlipidemic effect of ethanolic extract of aerial parts of Evolvulus alsinoides L. and its chloroform fraction in olive oil induced hyperlipidemic rats. The antihyperlipidemic activity of Evolvulus alsinoides was compared with a standard drug Atrovastatin (50mg/kg). The study involved phytochemical screening and chromatographic studies of extract and fraction. The ethanolic extract and its fraction were administered orally at doses of 200 and 400 mg/kg body weight in rats. Olive oil (5ml/kg oral dose) was administered 30 min after treatment. Blood was collected by ocular puncture 2 and 4 h after olive oil treatment and centrifuged at 3000 rpm for 15"20 min. Serum samples were further subjected to biochemical analysis. The study dose dependently inhibited the total cholesterol (TC) triglycerides (TG), low density lipoproteins (LDL) level, and significantly increased high density lipoprotein (HDL) level. Phytochemical screening revealed the presence of sterols, flavanoids, tannins and alkaloids. UV λmax was found to be 241 nm with a melting point of 137" 138 0 C for the isolated component. The antihyperlipidemic effect was evaluated in olive oil loaded rats. Acute treatment caused stimulatory effect on HDL level and inhibition in TC and TG elevation induced by olive oil. This drug is highly valued as traditional system of medicine. Allopathic drugs exert various side effects. Therefore it is cleared from the above study that medicinal plants have got potential to be used safely and can control the state of hyperlipidemia upto greater extent.
(2017) SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure. IEEE Transactions on Neural Networks and Learning

This paper presents an enhanced rank-order based learning algorithm, called SpikeTemp, for Spiking Neural Networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: an encoding layer which temporally encodes real valued features into spatio-temporal spike patterns, and an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rankorder based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and thus reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark datasets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms and the results demonstrate the ability of SpikeTemp to classify different datasets after just one presentation of the training samples with comparable classification performance.
Second Generation LHC Analysis Framework: Workload-based and User-oriented Solution

Consolidation and upgrades of accelerator equipment during the first long LHC shutdown period enabled particle collisions at energy levels almost twice higher compared to the first operational phase. Consequently, the software infrastructure providing vital information for machine operation and its optimisation needs to be updated to keep up with the challenges imposed by the increasing amount of collected data and the complexity of analysis. Current tools, designed more than a decade ago, have proven their reliability by significantly outperforming initially provisioned workloads, but are unable to scale efficiently to satisfy the growing needs of operators and hardware experts. In this paper we present our progress towards the development of a new workload-driven solution for LHC transient data analysis, based on identified user requirements. An initial setup and study of modern data storage and processing engines appropriate for the accelerator data analysis was conducted. First simulations of the proposed novel partitioning and replication approach, targeting a highly efficient service for heterogeneous analysis requests, were designed and performed.
Optimal Portfolio Selection with a Shortfall Probability Constraint: Evidence from Alternative Distribution Functions

We propose a new approach to optimal portfolio selection in a downside risk framework that allocates assets by maximizing expected return subject to a shortfall probability constraint, reflecting the typical desire of a risk-averse investor to limit the maximum likely loss. Our empirical results indicate that the loss-averse portfolio outperforms the widely used mean-variance approach based on the cumulative cash values, geometric mean returns, and average risk-adjusted returns. We also evaluate the relative performance of the loss-averse portfolio with normal, symmetric thin-tailed, symmetric fat-tailed, and skewed fat-tailed return distributions in terms of average return, risk, and average risk-adjusted return.
Interstate Cigarette Bootlegging: Extent, Revenue Losses, and Effects of Federal Intervention

We develop a model of commercial smuggling in which some firms smuggle a portion of the cigarettes they sell. The model is used to estimate the extent of smuggling across state lines and the effects of federal efforts to control smuggling via the Contraband Cigarette Act (CCA). We find that commercial smuggling accounted for three to four percent of all cigarettes sold during the 1970s, a decade of high excise tax differentials. Further, the CCA had the unintentional effect of increasing commercial smuggling, a result consistent with a change in enforcement and modes of smuggling reported subsequent to the Act.
A study for the influence of mosquitoes saliva on immunity of a laboratory animal (pigeon) to control infectious diseases.

The saliva of blood feeding arthropods has a variety of substances that are responsible for the success of blood meal. Repeated bites of mosquitoes stimulate immune responses to salivary antigen in the vertebrate host. In this study group of 4pigeons were exposed to frequent bites of groups of Culex pipiense and Anopheles pharoensis (100 female mosquitos per pigeon, 6 times in 18 weeks) and the biting rate were estimated. The biting rate of mosquitoes on pigeons decreased through different attempts. Group of 12 different clean pigeons are used as control pigeons (6 pigeons for each mosquito’s species) where one pigeon is exposed to the bites of 100 mosquitoes of one species 6 times in 18 weeks and the biting rate were calculated. The rate is relatively constant. The rate decreased in the case of the frequent bites may be due to the immunomodulative substances in mosquito saliva which stimulate immune responses in pigeons. Pigeons previously bitten frequently by Culex pipiense (Cx. sp.) and Anopheles pharoensis (An. sp.) mosquitoes are exposed once to bites of 100 female mosquitoes of the other mosquito species. The rate of feeding was calculated . This rate was increased. This increasing in the rate may be due to little cross- reactivity between the two mosquitoes species. Further investigations are recommended to study the effect of mosquito saliva on human immune responses to evaluate the mosquito salivary proteins as vaccines for mosquitoes-borne diseases and also for decreasing or prevent the biting of mosquitoes.
Perforating branches of the middle cerebral artery Microsurgical anatomy of their extracerebral segments

~" Perforating branches of the middle cerebral artery (MCA) were examined under magnification in 50 formalin-fixed brain hemispheres. Perforating vessels varied in number from three to 18, with an average of nine. The greater the number of vessels, the smaller was their diameter. In this study, the perforating arteries were divided into medial, middle, and lateral groupings. Those in the medial group usually arose directly from the MCA main trunk close to the carotid bifurcation. There were usually three vessels in the middle group, which originated not only from the MCA trunk, but also from the MCA collateral (cortical) branches. Common stems, when present, gave rise to individual perforating vessels and occasionally to thin olfactory and insular rami. Perforating arteries in the lateral group varied from one to nine in number. In addition to an origin from the MCA trunk, they also arose from cortical branches supplying the frontal and temporal lobes. The fact that lateral perforating vessels often originated from division sites and from terminal branches of the MCA is of clinical significance, because aneurysms are more commonly located at the MCA bifurcation. Anastomoses were not found among the perforating arteries. In two specimens, a fusion between a perforating artery and the MCA trunk was noted. Since the perforating vessels are obviously end arteries, injury to them must be avoided during operations for MCA aneurysms.
Citizen Science as an Ecological Research Tool: Challenges and Benefits

Citizen science, the involvement of volunteers in research, has increased the scale of ecological field studies with continent-wide, centralized monitoring efforts and, more rarely, tapping of volunteers to conduct large, coordinated, field experiments. The unique benefit for the field of ecology lies in understanding processes occurring at broad geographic scales and on private lands, which are impossible to sample extensively with traditional field research models. Citizen science produces large, longitudinal data sets, whose potential for error and bias is poorly understood. Because it does not usually aim to uncover mechanisms underlying ecological patterns, citizen science is best viewed as complementary to more localized, hypothesis-driven research. In the process of addressing the impacts of current, global “experiments” altering habitat and climate, large-scale citizen science has led to new, quantitative approaches to emerging questions about the distribution and abundance of organisms across spa.
A Broadband Terahertz Heterodyne Receiver with an NbN HEB Mixer

We present a broadband and low noise heterodyne receiver for 1.4-1.7 THz designed for the Hershel Space Observatory. A phononcooled NbN HEB mixer was integrated with a normal metal doubleslot antenna and an elliptical silicon lens. DSB receiver noise temperature Tr was measured from 1 GHz through 8GHz intermediate frequency band with 50 MHz instantaneous bandwidth. At 4.2 K bath temperature and at 1.6 THz LO frequency Tr is 800 K with the receiver noise bandwidth of 5 GHz. While at 2 K bath temperature Tr was as low as 700 K. At 0.6 THz and 1.1 THz a spiral antenna integrated NbN HEB mixer showed the receiver noise temperature 500 K and 800 K, though no antireflection coating was used in this case. Tr of 1100 K was achieved at 2.5 THz while the receiver noise bandwidth was 4 GHz.
Supporting the Creation of Some Class of Well-founded OWL-DL Ontologies

We present the method for creating semantically rich OWL-DL ontologies. Such ontologies contain a top part consisting of the most general concepts that are linked by carefully designed basic formal relations, which is why the ontologies are called well-founded. As the top part we apply the foundational paradigm of constructive descriptions and situations c.DnS known from literature, using it to obtain the method of a layered ontology creation. Every layer may contain ontological capsules, i.e. modules that are defined according to an expressive content pattern (formed on the basis of c.DnS), which makes the whole ontology well-founded. The method is equipped with the semantically strong computational tool that effectively supports a user in the process of creation and population of the considered well-founded ontologies.
SOME DRILLING PARAMETERS AS A TOOL TO PREDICT DIFFERENT CATEGORIES OF ROCKS

Experimental works have been performed on five types of limestone, two types of marble and two types of granite representing sedimentary, metamorphic and igneous rocks respectively. Rate of penetration (ROP) of diamond core drill with different thrust load and rotary speeds have been obtained. Drilling Specific energy (SE) has been determined in all types of rocks under investigation at different applied loads and rotary speeds. The results were obtained for rate of penetration (ROP) to show the variation in specific energy with the different rocks. A new dimensionless index UCS/SE (Uniaxial Compressive Strength divided by specific energy) was calculated and the rates of penetration against UCS/SE for all rocks were plotted. The interpretation of these relationships clears that at lower thrust loads and higher rotary speeds the three groups of rocks were classified distinctly as three categories. Whereas, at higher thrust loads and higher rotary speeds were clearly classified as two categories, one for sedimentary only and the other for metamorphic and igneous together. From these results with other information obtained by analysis of drill cuttings and the results that have been obtained from relationships, it can be possible to identify the rock type being drilled.
Consistency test for quantum process tomography

It is generally assumed that every process in quantum physics can be described mathematically by a completely positive map. However, experimentally reconstructed processes are not necessarily completely positive due to statistical or systematic errors. In this paper, we introduce a test for discriminating statistical from systematic errors which is necessary to interpret experimentally reconstructed, non-completely positive maps. We demonstrate the significance of the test using several examples given by experiments and simulations. In particular, we demonstrate experimentally how an initial correlation between the system to be measured and its environment leads to an experimentally reconstructed map with negative eigenvalues. These experiments are carried out using atomic Yb ions confined in a linear Paul trap, addressed and coherently manipulated by radio frequency radiation.
A PHYSIOLOGICAL METHOD FOR THE QUANTITATIVE MEASUREMENT OF MICROBIAL BIOMASS IN SOILS

A method is described for the rapid and objective estimation of the amount of carbon in the living, non-resting microbial biomass of soils. The method, which is based on the initial respiratory response of microbial populations to amendment with an excess of a carbon and energy source, was quantified using an expanded version of Jenkinson’s technique. The simultaneous application of the two methods to 50 soil samples showed a highly significant correlation (r = 0.96) between both, From this correlation it could be deduced that at 22°C a substrateinduced maximal respiratory rate of 1 ml CO*. h ’ corresponds to c. 40 mg microbial biomass C. Evidence supporting these results was obtained from pure culture studies. The various soil types investigated were collected from agricultural as well as forest sites and they contained between 15 and 240mg microbial C. IOOg dry soil-i. The respiratory method provides reproducible estimates of biomass size within l-3 h after soil amendment. It can be combined without difficulty with a seiective inhibition method for determination of bacterial and fungal contributions to soil metabolism.
An Empirical Study on the Impacts of Organizational Innovation on Performance of Nonprofit Organizations Based on QCA

Organizational innovation is particularly important as the soft power of nonprofit organization. This paper discloses that the improvement of performance of nonprofit organizations depends on the combination of different elements of organizational innovation instead of the strength of an element in organizational innovation; and the strength of organizational innovation elements in different nonprofit organizations varies. Based on 23 tertiary hospitals in Beijing, it employs qualitative comparative analysis (QCA) to make an empirical study of the impacts of organizational innovation on performance of nonprofit organizations. The study proves that the main factors to promote performance of nonprofit organizations are the combination of different elements of organizational innovation, including product innovation, process innovation, and management innovation. The optimal performance in nonprofit organizations for a collection of logic is: the introduction of new services or projects * organize new activities for customers, employees, or volunteers * the introduction of new service delivery + provide new training topics for employees or volunteers * adopt a new organizational structure * implement new recruitment of staff and volunteer.
The role of track stiffness and its spatial variability on long-term track quality deterioration

With rapid advances in sensor and condition monitoring technologies, railway infrastructure managers are turning their attention towards the promise that digital information and big data will help them understand and manage their assets more efficiently. In addition to the existing track geometry records, it is evident that track stiffness is a key physical quantity to help assess track quality and its long-term deterioration. The present paper analyses the role of track stiffness and its spatial variability through a set of computational experiments, varying other vehicle and track physical quantities such as vehicle unsprung mass, speed and track vertical irregularities. The support stiffness conditions are obtained using a sample procedure from an autoregressive integrated moving average model to generate a representative larger set of data from previously on-site measured data. A set of computational experiments is carefully designed, varying different physical variables, and a vehicle–track interaction model is used to estimate the track geometry deterioration rates. A series of log-linear regression models are then used to analyse the impact of the tested physical variables on the track deterioration. The main findings suggest that the spatial variability of track stiffness significantly contributes to the track deterioration rates, and thus it should be used in the future to better target the design and maintenance of railway track. Finally, a comparative study of some settlement models available in literature shows that they are very dependent on the test conditions under which they have been derived.
Random variate generation from Multivariate Exponential Power distribution

Summary: In this paper two procedures for random variate generation for the family of Multivariate Exponential Power (MEP) distributions are developed and then compared. By conveniently expressing MEP distributions in terms of mixture of random variables, a simple and fast procedure based on transformation approach is proposed. Another procedure, based on a general acceptance-rejection (AR) technique for multivariate orthounimodal densities, is considered. As expected, the transformation-based procedure is considerably less time-consuming than the other one. Furthermore, this study allows us to evaluate to which extent generalizations of AR methods could be computationally less efficient than a transformation one for the type of multivariate distributions considered.
Graphene Oxide/Reduced Graphene Oxide Aerogels

In this chapter, we will discuss aerogels based on graphene oxide/reduced graphene oxide—promising composite materials, based on 2D carbon nanoparticles, with a certain architecture that prevents aggregation of graphene layers with a highly developed sur- face that have a high potential technological realization as materials for supercapacitors, sensors, batteries, and actuators. This chapter describes the existing methods for produc - ing composite aerogels based on graphene oxide/reduced graphene oxide, the structural features of these materials, the most relevant studies in the areas of surface modification, architectural control, improvement of mechanical properties, and the most interesting applications. It has been shown that such materials have relatively high specific surface values and a high degree of exfoliation of graphene layers, but an urgent need is to improve them, which is due to the fragility of graphene aerogels and composite materials based on them, as well as the need to modify the surface to control porosity.