Miracle-dz/UniFAR-FTUs huggingface dataset:
Cosmic ray acceleration in superbubbles and the composition of cosmic rays

We review the evidence for cosmic ray acceleration in the superbubble/hot phase of the interstellar medium, and discuss the implications for the composition of cosmic rays and the structure and evolution of the interstellar medium (ISM). We show that the bulk of the galactic supernovae, their expanding remnants, together with their metal-rich grain and gas ejecta, and their cosmic ray accelerating shocks, are all confined within the interiors of hot, low-density superbubbles, generated by the multiple supernova explosions of massive stars formed in giant OB associations. This superbubble/hot phase of the ISM provides throughout the age of the Galaxy a cosmic ray source of essentially constant metallicity for acceleration by the shocks of many supernovae over time scales of a few Myr, consistent with both Be/Fe evolution and ACE observations of 59Ni/59Co. We show that the expected metallicity (>2 times Solar) and filling factor (>50%) of the superbubble/hot phase is high enough that the composition of cosm.
Anu Raninen Practical Process Improvement How to Initiate Software Process Improvement in a Small Company

Nowadays, when software has become part of most everyday appliances, the significance of the software industry and especially small software companies is growing. The vast majority of companies world-wide are Small or Medium-sized Enterprises (SMEs). In Finland, over half of the software companies have only two to ten employees. Improving the operations of a company is necessary in order to maintain its competitive edge. Software Process Improvement (SPI) activities have been reported to result in remarkable improvements in the quality of software, reduced time to market and increased productivity. However, despite the evidence suggesting that the size of the organization does not limit its potential for SPI success, small companies (SCs) have been somewhat neglected by the SPI research community. The techniques and standards developed to support SPI are generally aimed at the larger organizations. As a result, small software companies struggle to initiate their improvement projects. The aim of this thesis is to provide a validated, practical, and easy to apply approach for small software companies to cost-effectively initiate SPI. The research is driven by close collaboration with SMEs undergoing SPI. Several case studies were conducted to develop and validate such an approach. The main contribution of the thesis is LAPPI, a light-weight technique to practical process modeling and improvement target identification. The LAPPI technique enables small software companies to initiate SPI cost-effectively. LAPPI is complemented by research into motivation monitoring, a recommended practice that supports the initiation and success of SPI initiatives in SCs. The contribution of the thesis is beneficial for stakeholders of SPI projects in small companies. The results are especially applicable in cases where companies are having trouble initiating SPI or have concerns about the cost of implementing SPI. Universal Decimal Classification: 004.41, 004.413, 005.62, 334.713 INSPEC Thesaurus: software engineering; software process improvement; software quality; small-to-medium enterprises; human factors Yleinen suomalainen asiasanasto: ohjelmistoala; ohjelmistokehitys; ohjelmistotuotanto; tietotekniikkayritykset; pienyritykset; prosessit; kehittäminen; mallintaminen; motivaatio
A global Eta model on quasi‐uniform grids

The application of quasi‐uniform grids in global models of the atmosphere is an attempt to increase the computational efficiency by a more cost‐effective exploitation of the computing infrastructure. This paper describes the development of a global version of NCEP's regional, step‐coordinate, Eta model on two quasi‐uniform grids: cubic and octagonal. The governing equations are expressed in a general curvilinear form, so that the cubic and the octagonal versions of the model share the same code in spite of different mapping of the computational domain.
Checkpointing of Rectilinear Growth in DNA Self-Assembly

Error detection/correction techniques have been advocated for algorithmic self-assembly. Under rectilinear growth, it requires only two additional tiles, generally referred to as Isolation tiles. This process can be effectively utilized for checkpointing and is analyzed in this paper self-assembly. Initially, the physical framework (and related features) for the removal of the erroneous sections of an assembly is outlined. A novel Markov based model is presented to establish the optimal rate of checkpointing and assess its performance versus other error tolerant techniques that utilize redundancy. Simulation results are provided.
Complexity and cohomology for cut-and-projection tilings

Abstract We consider a subclass of tilings: the tilings obtained by cut-and-projection. Under somewhat standard assumptions, we show that the natural complexity function has polynomial growth. We compute its exponent α in terms of the ranks of certain groups which appear in the construction. We give bounds for α. These computations apply to some well-known tilings, such as the octagonal tilings, or tilings associated with billiard sequences. A link is made between the exponent of the complexity, and the fact that the cohomology of the associated tiling space is finitely generated over ℚ. We show that such a link cannot be established for more general tilings, and we present a counterexample in dimension one.
The effect of using welfare IT convergence contents on physical function, depression, and social participation in the elderly

[Purpose] This study investigates the effects of welfare IT convergence contents on physical function, depression, and social participation among the elderly. It also aims to provide material for future activity mediation for the elderly. [Subjects] Two hundred subjects >65 years were selected from six elderly welfare facilities and related institutions in the Busan and Gyeongbuk areas and were evaluated from 2014 to 2015. [Methods] This study assessed physical function, depression, and social participation; 100 subjects who utilized commercialized welfare IT convergence contents were included in an experimental group and 100 subjects who had no experience thereof were included in a control group. [Results] When comparing differences in physical function between the groups, balance maintenance was better in the experimental group. There were also significant differences in depression and social participation. The experimental group displayed higher physical function, lower depression levels, and higher social participation levels compared to the control group. [Conclusion] Welfare IT convergence contents positively influence occupational performance in the elderly. Future research is necessary to provide information to the elderly through various routes, so that they can understand welfare IT convergence contents and actively utilize them.
Verifying security patches

In this paper, we introduce a formal framework for ensuring the correctness of security patches. We discuss the issues and provide a sketch of how one could implement a system that proves (in many cases) or provides robust evidence (in other cases) that a security patch fixes a bug, and changes nothing else about the semantics of a program. We make use of an analysis of "bug surfaces" the set of inputs that trigger a bug, to give a type theoretic characterization of the non-buggy surface of a program. We thus give credence to the Langsec notion that security flaws are often about input handling, and show how formal patch and bug analysis can be used to define a more correct input type for a program.
A Similarity-Based Learning Algorithm Using Distance Transformation

Numerous theories and algorithms have been developed to solve vectorial data learning problems by searching for the hypothesis that best fits the observed training sample. However, many real-world applications involve samples that are not described as feature vectors, but as (dis)similarity data. Converting vectorial data into (dis)similarity data is more easily performed than converting (dis)similarity data into vectorial data. This study proposes a stochastic iterative distance transformation model for similarity-based learning. The proposed model can be used to identify a clear class boundary in data by modifying the (dis)similarities between examples. The experimental results indicate that the performance of the proposed method is comparable with those of various vector-based and proximity-based learning algorithms.
PACKAGING POLICIES TO ADDRESS ENVIRONMENTAL CONCERNS. IN: HANDBOOK OF TRANSPORT AND THE ENVIRONMENT

This chapter looks at measures needed to implement strategies addressing transport externalities. The ways to identify measures that enhance effectiveness are reviewed. As the number of goals affects the complexity of the task, this chapter differentiates between single-and multiple-goal strategies. A discussion of the considerations in identification of mitigation measures that may enhance the political acceptability of policy packages is provided. Timing, scale, and institutional issues are raised. Thus, each secton contributes to the overall formulation of strategies to address transport externalities. Lastly, a brief overview is included of the questions that should be dealt with when packaging policies into coherent strategies.
Wireless power transmission using modulated microwave

A microwave power beaming system was developed to realize wireless power supply to a Micro Aerial Vehicle. This system consists of transmitting, tracking, and receiving systems. In the transmitting system, a 5.8GHz microwave beam was irradiated from an active phased array antenna. Transmitting power was 4W and the beam divergence angle was 9deg. In the tracking system, a 2.45GHz pilot signal was detected by a two-dimensional tracking antenna and the position was deduced though the software retro-directive function. The maximum tracking error was 1.97deg in the azimuth direction and 1.79deg in the traverse direction. Then, FM/AM wireless camera signal was used the pilot signal for tracking. The maximum error was 3.22deg in the traverse direction and was 4.97deg in azimuth direction that were slightly larger than those without modulation.
Brain tumor detection from MR images: Image processing, slicing and PCA based reconstruction

In this paper, a novel algorithm is developed to feature out tumor from diseased brain Magnetic Resonance (MR) images. In this work, based on a study of quality parameter comparison of two filters, adaptive median filter is selected for de-noising the images. Image slicing and identification of significant planes are done. Logical operations are applied on selected slices to obtain the processed image showing the tumor region. A novel image reconstruction algorithm is developed based on the application of Principal Components Analysis (PCA). This reconstruction algorithm is applied on original raw images as well as on the processed images. Results of this work confirm the sole efficiency of the developed image processing algorithm to detect brain tumor. For this work randomly chosen 20 normal brain MR images and 20 brain tumor MR images are considered. Also in this work, statistical significance testing is carried out to justify the uniformity of population means of the processed output. Finally normal and processed outputs are compared.
Computational Statistics and Data Analysis Gaussian Process Hyper-parameter Estimation Using Parallel Asymptotically Independent Markov Sampling

Gaussian process emulators of computationally expensive computer codes provide fast statistical approximations to model physical processes. The training of these surrogates depends on the set of design points chosen to run the simulator. Due to computational cost, such training set is bound to be limited and quantifying the resulting uncertainty in the hyper-parameters of the emulator by uni-modal distributions is likely to induce bias. In order to quantify this uncertainty, this paper proposes a computationally efficient sampler based on an extension of Asymptotically Independent Markov Sampling, a recently developed algorithm for Bayesian inference. Structural uncertainty of the emulator is obtained as a by-product of the Bayesian treatment of the hyper-parameters. Additionally, the user can choose to perform stochastic optimisation to sample from a neighbourhood of the Maximum a Posteriori estimate, even in the presence of multimodality. Model uncertainty is also acknowledged through numerical stabilisation measures by including a nugget term in the formulation of the probability model. The efficiency of the proposed sampler is illustrated in examples where multi-modal distributions are encountered. For the purpose of repro-ducibility, further development, and use in other applications the code used to generate the examples is freely available for download at https://github.com/agarbuno/paims_codes.
Sequencing of 50 Human Exomes Reveals Adaptation to High Altitude

No Genetic Vertigo Peoples living in high altitudes have adapted to their situation (see the Perspective by Storz). To identify gene regions that might have contributed to high-altitude adaptation in Tibetans, Simonson et al. (p. 72, published online 13 May) conducted a genome scan of nucleotide polymorphism comparing Tibetans, Han Chinese, and Japanese, while Yi et al. (p. 75) performed comparable analyses on the coding regions of all genes—their exomes. Both studies converged on a gene, endothelial Per-Arnt-Sim domain protein 1 (also known as hypoxia-inducible factor 2α), which has been linked to the regulation of red blood cell production. Other genes identified that were potentially under selection included adult and fetal hemoglobin and two functional candidate loci that were correlated with low hemoglobin concentration in Tibetans. Future detailed functional studies will now be required to examine the mechanistic underpinnings of physiological adaptation to high altitudes. Sequencing coding regions identified genetic changes that were likely involved in adaptation to hypoxia. Residents of the Tibetan Plateau show heritable adaptations to extreme altitude. We sequenced 50 exomes of ethnic Tibetans, encompassing coding sequences of 92% of human genes, with an average coverage of 18× per individual. Genes showing population-specific allele frequency changes, which represent strong candidates for altitude adaptation, were identified. The strongest signal of natural selection came from endothelial Per-Arnt-Sim (PAS) domain protein 1 (EPAS1), a transcription factor involved in response to hypoxia. One single-nucleotide polymorphism (SNP) at EPAS1 shows a 78% frequency difference between Tibetan and Han samples, representing the fastest allele frequency change observed at any human gene to date. This SNP’s association with erythrocyte abundance supports the role of EPAS1 in adaptation to hypoxia. Thus, a population genomic survey has revealed a functionally important locus in genetic adaptation to high altitude.
How Pro-Poor and Progressive is Social Spending in Zambia?

This paper analyzes the distributional effect of public spending in Zambia using the most recent data from the 2010 Living Conditions Monitoring Survey. The analysis focuses on both the"traditional"social sectors, such as education and public healthcare, as well as other spending areas less thoroughly studied, such as agricultural support programs. Ultimately, this benefit incidence analysis addresses the extent to which spending is pro-poor and progressive; that is, it primarily benefits the poor and does so at an increasing rate as welfare levels decrease. The results indicate that overall public education spending in Zambia is neither pro-poor nor progressive, but while this is true for the system as a whole it is not true for all of its parts. The net unitary benefits of primary and secondary education are clearly both pro-poor and progressive. However, their progressivity is ultimately outweighed by the extreme concentration of tertiary education benefits among the wealthiest members of Zambian society. Health spending is also regressive and not pro-poor. Although unitary net benefits are slightly progressive, unequal access remains the key constraint. In contrast, the benefits of agricultural-input subsidy programs follow a somewhat progressive pattern (for each beneficiary in the top quintile there are almost two beneficiaries in the poorest quintile) but clearly suffer from targeting problems. Consequently, without better-designed and more conscientiously implemented targeting mechanisms, public spending on health, education, and fertilizers will not be able to further the government's larger objectives for pro-poor and progressive development policy.
Stress recognition in human-computer interaction using physiological and self-reported data: a study of gender differences

This paper investigates gender differences in stress recognition in human computer interaction (HCI) for both objective (i.e., skin conductance) and subjective (i.e., valence-arousal VA ratings) metrics. To this end, 31 healthy participants, 18 females, performed five HCI tasks, while their skin conductance was recorded. These selected HCI tasks were the ones listed as the most stressful, by a group of typical computer users, who were involved in a face to face pre-experiment interview for the identification of stressful cases in computer interaction. After each task, participants rated their interaction experience using the valence-arousal scale. The collected data were split based on participants' gender. Skin conductance signals were analyzed using seven popular machine learning classifiers. In both groups the best stress recognition accuracy for all tasks was achieved by Linear Discriminant Analysis LDA; Males: Mean=94.8% and SD=1.5%, Females: Mean=98.9% and SD=0.3%. Self-reported data analysis revealed a significant difference on how both genders communicate their emotions using the arousal scale. Our findings tend to suggest that gender does not affect skin conductance data during subtle HCI tasks. However subjective ratings such as arousal of emotional experience must be utilized carefully.
Multifrequency simultaneous bioimpedance measurements using multitone burst signals for dynamic tissue characterization

In this paper we present the keypoints to perform multifrequency simultaneous bioimpedance measurements using multitone signals. Concerning the frequency distribution, tones are spread over 1kHz to 1MHz range using a custom frequency distribution which we called Bilateral Quasi Logarithmic (BQL). BQL concentrates a higher number of tones around the impedance relaxation and contains a frequency plan algorithm. It minimizes the intermodulation effects due to non-linearities behaviours of the DUT and electrodes by slightly shifting the original tones in order to guarantee a guard bandwith. Regarding the multitone phase distribution, a Genetic Algorithm (GA) has been developed to minimize multitone Crest Factor (CF). This allow us to maximize the resultant Signal to Noise Ratio (SNR) of the acquisition system. This paper also presents the relation between parameters such as sampling frequency and ADC bits with the SNR and the effect in the overall amplitude and phase error when using multitone signals as excitation waveforms. Finally, we present characterization results from a measurement system based on a modular PXI architecture.
MPEG-2 Compressed-Domain Algorithms for Video Analysis

This paper presents new algorithms for extracting metadata from video sequences in the MPEG-2 compressed domain. Three algorithms for efficient low-level metadata extraction in preprocessing stages are described. The first algorithm detects camera motion using the motion vector field of an MPEG-2 video. The second method extends the idea of motion detection to a limited region of interest, yielding an efficient algorithm to track objects inside video sequences. The third algorithm performs a cut detection using macroblock types and motion vectors.
Emu: Getting the End-Game Right

By spring 1998, an agreement must be reached on the first group of European countries to participate in the economic and monetary union (EMU). If all goes according to plan, EMU itself will begin on January 1, 1999. Written by a team of distinguished European academics, this report looks at this final stage of the transition to monetary union. The authors consider whether the current ERM rule should continue to operate between the announcement and the start of EMU. They also assess when the new exchange rate system (EMS-2) designed to link " ins" and " pre-ins" should start operating. Their analysis and conclusions will continue to influence the conduct of monetary policy long after the 1998 decision.
Application of neural networks for filtering non-impact transients recorded from biomechanical sensors

A number of biomechanical sensor applications are available on the market today for sports, as well as military applications. These sensors are capable of measuring accelerations and velocities of impact that may be useful for understanding head and neck biomechanics; although the proper use and accuracy of these analysis techniques is still a topic of research. A challenge with these sensors is filtering the raw data to include authentic impacts and exclude false events that are sometimes registered due to the sensitivity of the sensors. In this study we have developed an algorithm based on artificial neural networks and discrete fourier transform based filtering that will be used to distinguish between a biomechanically relevant event and a non-impact transient which is of no concern. Linear accelerations and angular velocities are used as inputs to the pattern recognition algorithm and the output vector contains the probability of each impact belonging to a certain class. Using this approach we report a specificity of 47% and a sensitivity of 88% in the ability to distinguish between real impacts and non-impact transients.
Owner Motivations in the UK Speciality Food Sector

This paper investigates empirically whether owner motivations are consistent with neoclassical models of profit maximisation. Contrary to the neoclassical model, in some markets owners gain private benefits from supplying products with certain characteristics. To consider this issue, a full theoretical model that allows owners to consider not only profit, but also utility, in their choices of price, product quality, and the use of an owner-specific production method was developed. Information was gathered on owner motivations from the UK speciality food sector to test the propositions of the theoretical model. Evidence of systematic utility maximisation is found and utility maximising owners set higher profit maximising prices and produce a higher quality product. These findings have implications for the UK speciality food sector.