Miracle-dz/UniFAR-FTUs huggingface dataset:
Potential Energy Surfaces and Rates of Spin Transitions

Abstract The stability of magnetic states and the mechanism for magnetic transitions can be analyzed in terms of the shape of the energy surface, which gives the energy as a function of the angles determining the orientation of the magnetic moments. Minima on the energy surface correspond to stable or metastable magnetic states and can represent parallel, antiparallel or, more generally, non-collinear arrangements. A rate theory has been developed for systems with arbitrary number, N, of magnetic moments, to estimate the thermal stability of magnetic states and the mechanism for magnetic transitions based on a transition state theory approach. The minimum energy path on the 2N-dimensional energy surface is determined to identify the transition mechanism and estimate the activation energy barrier. A pre-exponential factor in the rate expression is obtained from the Landau–Lifshitz–Gilbert equation for spin dynamics. The velocity is zero at saddle points so it is particularly important in this context to realize that the transition state is a dividing surface with 2N − 1 degrees of freedom, not just a saddle point. An application of this rate theory to nanoscale Fe islands on W(110) has revealed how the transition mechanism and rate depend on island shape and size. Qualitative agreement is obtained with experimental measurements both for the activation energy and the pre-exponential factor. In particular, a distinct maximum is observed in the pre-exponential factor for islands where two possible transition mechanisms are competing: Uniform rotation and the formation of a temporary domain wall. The entropy of the transition state is enhanced for those islands making the pre-exponential factor more than an order of magnitude larger than for islands were only the uniform rotation is viable.
Validity and reliability of the Dutch version of the Camberwell Assessment of Need for the Elderly in community-dwelling people with dementia

ABSTRACT Background: Tailor-made care in dementia requires an individual needs assessment. The Camberwell Assessment of Need for the Elderly (CANE) was developed to assess needs of older people with mental disorders. In this study the validity and reliability of the Dutch version of the CANE were studied among community-dwelling persons with dementia and their informal carers. Method: Interviews were carried out with 236 people with mild to severe dementia and 322 informal carers; 69 informal carers were interviewed twice. Construct and criterion validity and test-retest reliability of the CANE were studied using data for informal carers. Construct validity was also studied for CANE ratings of people with dementia. Results: The construct validity of the CANE was good among people with dementia and informal carers. Criterion validity could be studied for 76.9% of the CANE items, and all significant correlations were convergent. Test-retest reliability of the CANE varied from poor to very good and was best on domains where needs were explicit and problems well defined. Conclusions: Use of the Dutch version of the CANE among community-dwelling people with dementia and their carers is supported by the study results, with the study showing acceptable construct and criterion validity and test-retest reliability of the CANE.
RNA Is Closely Associated with Human Mast Cell Secretory Granules, Suggesting a Role(s) for Granules in Synthetic Processes

The distribution of ribosomes in mature human mast cells, a major granulated secretory cell, does not resemble that in other secretory cells, such as pancreatic acinar cells and plasma cells. By routine ultrastructural analysis, ribosomes in human mast cells are often close to, attached to, or even appear to be within secretory granules. To document better these relationships, we used multiple electron microscopic imaging methods, based on different principles, to define RNA, ribosome, and granule relationships in mature human mast cells. These methods included EDTA regressive staining, RNase digestion, immunogold labeling of ribonucleoproteins or uridine, direct binding or binding after ultrastructural in situ hybridization of various polyuridine probes to polyadenine in mRNA, and ultrastructural autoradiographic localization of [3H]-uridine incorporated into cultured human mast cells. These different labeling methods demonstrated ribosomes, RNA, U1SnRNP (a small nuclear RNP specific for alternative splicing of mRNA), mRNA, and uridine to be associated with secretory granules in human mast cells, implicating granules in a larger synthetic role in mast cell biology.
Monolithic integration of vertical-cavity laser diodes and resonant photodetectors with hybrid Si3N4-SiO2 top Bragg mirrors

Top-emitting vertical-cavity surface-emitting lasers are monolithically integrated with resonance enhanced photodetectors (REPDs), utilizing dielectric Si/sub 3/N/sub 4/-SiO/sub 2/ top Bragg mirrors. High-efficiency (66%) REPDs with a narrow optical bandwidth of 1.25 nm were realized by adjusting the incoupling mirror's reflectivity. High-finesse REPDs with low QW-absorption, have smaller efficiencies (/spl sim/10%), but extremely narrow optical bandwidths down to 0.196 nm. The high spectral resolution of these detectors leads to the appearance of higher-order transverse detector modes in the spectral response.
Critical success factors for business intelligence system implementation

Hirsimäki, Renne Henry Oskari Critical Success Factors for Business Intelligence System Implementation Jyväskylä: University of Jyväskylä, 2017, 24 p. Information Systems Science, Bachelor’s thesis Supervisor: Seppänen, Ville Business intelligence (BI) helps organisations to make better and faster decisions. BI system can be seen as an integrated set of tools, technologies and software to support the decision-making. These systems are complex and their implementation has high risks and require a lot of time, money and effort, and therefore it is important to identify the factors that support the successful implementation. This thesis focused on recognising the critical success factors (CSFs) for BI system implementation, and understanding why they are important. The CSFs were found and further analysed based on existing literature. The most important CSFs were categorised in organisational, process and technological dimensions. The CSFs from the organisational dimension were clear vision and well-established business case, committed management support and sponsorship, and understanding of organisational culture. From the process dimension the most crucial CSFs were appropriate team skills, user-oriented change management, and user training and support. And from the technological dimension business driven, scalable and flexible framework; sustainable data quality, accuracy and integrity; and understanding the firms needs, requirements and processes were identified as most vital. The most interesting observation of this study is that many of the CSFs have interrelations and are somehow dependent on each other.
Government support and firm financial performance: New evidence from a transitional economy

Using a panel dataset of five waves of private manufacturing SMEs surveys in the period 2007-15, this paper contributes to literature by considering for the first time the effects of government support on firms’ financial performance in Vietnam. Interestingly, contrary to the many findings of previous studies, we find that government assistance affect firms’ financial performance after controlling for heterogeneity, unobservable factors and dynamic endogeneity. This finding supports for the viewpoints of institutional theory. Also, the study shows that technical supports from government such as export promotion, human resource training and technology programmes have insignificant linkages with firm financial performance, but financial supports play an important role, suggesting that supporting measures as tax exemptions, soft loans and investment incentives promote financial efficiency and are vital for the development of Vietnamese private SMEs.
Nonparametric Framework for Detecting Spectral Anomalies in Hyperspectral Images

Over the past few years, hyperspectral data exploitation aimed at detecting spectral anomalies within remotely sensed images has been of growing interest in many applications. In this letter, we are interested in an anomaly detection (AD) scheme for hyperspectral images in which spectral anomalies are defined with respect to a statistical model of the background probability density function (PDF). Among the multitude of PDF estimators discussed in statistics literature, Parzen windowing (PW) has always attracted much attention. However, its ability to estimate the PDF of global background in order to detect anomalies in hyperspectral images has not been investigated yet. Here, we propose the use of PW to provide reliable background PDF estimation. As is widely recognized, PW performance is primarily affected by the choice of the bandwidth matrix, which controls the degree of smoothing for the resulting PDF approximation. In this letter, the bandwidth selection problem is approached, resorting to an unsupervised method based on a Bayesian approach. Once the background PDF is approximated through PW, it is employed to detect anomalous objects within the scene by using the likelihood ratio test.
Bi-modal assistance functions and their effect on user perception and movement coordination with telesurgery systems

Aiming to ascertain the effects of uni- and bi-modal (visuo-haptic) assistance functions on movement coordination with a teleoperated surgical system (DLR's MiroSurge), an experimental user study was conducted with 36 participants. Since the literature suggests a link between task performance with assistance functions and certain user perceptions, the participants' preferences and perceptions of the assistance functions' helpfulness were also of interest. The results indicate that more users considered the bi-modal assistance helpful than the uni-modal assistance, even though this was not supported by quantitative measures of task performance. Overall, haptic assistance was preferred to visual assistance, presumably as it is considered less obtrusive. The results of this study offer important implications for the design of user assistance functions in teleoperation systems.
Bayesian Analysis for Dynamic Generalized Linear Latent Model with Application to Tree Survival Rate

Logistic regression model is the most popular regression technique, available for modeling categorical data especially for dichotomous variables. Classic logistic regression model is typically used to interpret relationship between response variables and explanatory variables. However, in real applications, most data sets are collected in follow-up, which leads to the temporal correlation among the data. In order to characterize the different variables correlations, a new method about the latent variables is introduced in this study. At the same time, the latent variables about AR (1) model are used to depict time dependence. In the framework of Bayesian analysis, parameters estimates and statistical inferences are carried out via Gibbs sampler with Metropolis-Hastings (MH) algorithm. Model comparison, based on the Bayes factor, and forecasting/smoothing of the survival rate of the tree are established. A simulation study is conducted to assess the performance of the proposed method and a pika data set is analyzed to illustrate the real application. Since Bayes factor approaches vary significantly, efficiency tests have been performed in order to decide which solution provides a better tool for the analysis of real relational data sets.
Quantitative detection of Sphingomonaschlorophenolica in soil via competitive polymerase chain reaction

The 16S ribosomal RNA gene sequence of the pentachlorophenol degrader Sphingomonas chlorophenolica strain RA2 was used to generate specific polymerase chain reaction (PCR) primers for the detection of this strain in soil, whereas a region internal to the two primers was used to provide an S. chlorophenolica strain RA2‐specific oligonucleotide probe. The PCR detection system resulted in a 727 bp product detectable via gel electrophoresis and hybridization. It was specific for strain RA2 and its close relative, S. chlorophenolica ATCC 39723, as evidenced by PCR amplifications of a range of bacterial genomic DNAs. Tests of total microbial community DNA obtained from five uninoculated and two RA2‐inoculated soils confirmed this specificity for introduced S. chlorophenolica RA2. Strain RA2 could be detected in soil down to a level of 103 cfu g−1 soil. Two strategies were followed to generate internal standard DNA for competitive PCR. First, a 479 bp MIMICS fragment was obtained based on a previously constructed gene cassette; however, this standard did not reliably quantify RA2 targets. Low stringency PCR performed with a range of bacterial genomic DNAs resulted in the generation of an amplicon with a Paenibacillus azotofixans strain that was slightly smaller than the RA2‐derived product. Both products were easily separable via conventional gel electrophoresis. The use of this competitor in a threefold dilution scheme applied to the target DNA allowed for the quantitative detection of RA2‐specific target DNA molecules from pure culture and from soil. The fate of strain RA2 in pentachlorophenol‐contaminated soil was described using this competitive PCR approach, and the organism was shown to persist at two inoculum levels over prolonged periods of time.
Fully integrated high voltage charge pump for energy-efficient reconfigurable multi-band RF-transceivers

This paper presents a fully integrated high voltage charge pump which enables a reconfigurable, energy-efficient multi-band transceiver. Using a high voltage CMOS technology from Austriamicrosystems and a 4-phase charge-pump (DC/DC converter) circuit architecture, up to 120 V supply voltage can be generated from a 3.7 V DC battery using this monolithically integrated circuit. The very small footprint of this solution enables the integration of this multi-band transceiver in mobile devices, whereas the concept of reconfigurability can also be applied to fixed transceiver installations to optimize power efficiency.
Bigdata Driven Cloud Security: A Survey

Cloud Computing (CC) is a fast-growing technology to perform massive-scale and complex computing. It eliminates the need to maintain expensive computing hardware, dedicated space, and software. Recently, it has been observed that massive growth in the scale of data or big data generated through cloud computing. CC consists of a front-end, includes the users’ computers and software required to access the cloud network, and back-end consists of various computers, servers and database systems that create the cloud. In SaaS (Software as-a-Service – end users to utilize outsourced software), PaaS (Platform as-a-Service-platform is provided) and IaaS (Infrastructure as-a-Service-physical environment is outsourced), and DaaS (Database as-a-Service-data can be housed within a cloud), where leading / traditional cloud ecosystem delivers the cloud services become a powerful and popular architecture. Many challenges and issues are in security or threats, most vital barrier for cloud computing environment. The main barrier to the adoption of CC in health care relates to Data security. When placing and transmitting data using public networks, cyber attacks in any form are anticipated in CC. Hence, cloud service users need to understand the risk of data breaches and adoption of service delivery model during deployment. This survey deeply covers the CC security issues (covering Data Security in Health care) so as to researchers can develop the robust security application models using Big Data (BD) on CC (can be created / deployed easily). Since, BD evaluation is driven by fast-growing cloud-based applications developed using virtualized technologies. In this purview, MapReduce [12] is a good example of big data processing in a cloud environment, and a model for Cloud providers.
Intelligent Classification Hazardous Gas Using Sensors Array

This paper presents an environmental pollution monitoring solution using intelligent classification system. Air is one the basic needs for human and other species in our natural ecosystem. Air quality may affect the harmonious ecosystem of human and living species that presence in the surrounding environment. The rapid growth of heavy modern industries is one of the factors that contributes to air quality contamination. A heavy industry such an oil and gas process plant may sometimes involves in unavoidable accident of pipeline leakage that polluting natural air. Hence, there is a need to introduce a scientific air quality classifier based on chemical array sensors. Electronic Nose (E-nose) is one of the chemical-based sensor arrays instruments which has a capability to measure odorprofile based sample data. Several intelligent classification systems can be employed in E-nose. In this work, an intelligent classification system namely Case Based Reasoning (CBR) technique was employed. The experimental results show that the intelligent classification technique using CBR has successfully classified the hazardous gas (butane and hexane) odor-profile with 78.3% rate of accuracy. 
Mapping Czech and English Valency Lexicons: Preliminary Report

We describe here a very first attempt to connect two valency lexicons: Pattern Dictionary of English Verbs (PDEV) and VerbaLex. Both lexicons contain verbs together with their syntactic structure (arguments of the verbal predicate) and semantic restrictions (semantic types typical for a given verb argument). The lexicons are similar in overall but differ in details since their formalisms are tailored for the respective languages. They also differ in a way they have been built: whilst the former resource has been built using Corpus Pattern Analysis methodology the latter has been built upon previous datasets Brief, Vallex and Czech WordNet. We present a preliminary work on linking English patterns in PDEV with their Czech equivalents: frames in VerbaLex.
Market-based autonomous and elastic application execution on clouds. (Gestion autonome des ressources et des applications dans un nuage informatique selon une approche fondée sur un marché)

Organizations owning HPC infrastructures are facing difficulties in managing their resources. These difficulties come from the need to provide concurrent resource access to different application types while considering that users might have different performance objectives for their applications. Cloud computing brings more flexibility and better resource control, promising to improve the user’s satisfaction in terms of perceived Quality of Service. Nevertheless, current cloud solutions provide limited support for users to express or use various resource management policies and they don't provide any support for application performance objectives.In this thesis, we present an approach that addresses this challenge in an unique way. Our approach provides a fully decentralized resource control by allocating resources through a proportional-share market, while applications run in autonomous virtual environments capable of scaling the application demand according to user performance objectives.The combination of currency distribution and dynamic resource pricing ensures fair resource utilization.We evaluated our approach in simulation and on the Grid'5000 testbed. Our results show that our approach can enable the co-habitation of different resource usage policies on the infrastructure, improving resource utilisation.
On the Average Rate of Quasi-Static Fading Channels with ARQ and CSI Feedback

This letter studies the effect of channel side information on the achievable rates of quasi-static fading channels. The side information is obtained via combination of the standard channel state information (CSI) and automatic repeat request (ARQ) feedback. Demonstrating the general rate optimization problem, the results are obtained for different power allocation strategies. Simulation results show that considerable rate increment is achieved with as low as one bit feedback for each of these approaches.
Three-Dimensional Finite-Element Mode-Solver for Nonlinear Periodic Optical Waveguides and Its Application to Photonic Crystal Waveguides

A 3-D finite-element mode-solver, based on a self-consistent algorithm, is newly developed for nonlinear periodic optical waveguides. The developed method makes it possible to calculate various nonlinear characteristics based on optical Kerr effect rigorously, including the nonlinear phase shift, the nonlinear refractive index distribution, and γ-value. Its validity is confirmed by analyzing a silicon-nanowire waveguide and a slot waveguide. To show the usefulness of the method, the nonlinear characteristics of photonic crystal line-defect waveguides and 1-D photonic crystal coupled resonator optical waveguides are investigated. Numerical results show that in some cases, γ-value calculated by the newly developed method and approximate linear analysis differs two-orders of magnitude. For instance, γ-value calculated by developed method is 510 000 m-1W -1 for a 1-D photonic crystal coupled resonator optical waveguide, whereas γ-value calculated by conventional method is only 5000 m-1W-1. This difference indicates that, to estimate the nonlinear characteristics of 3-D waveguides precisely, the developed nonlinear guided mode solver is required.
Methionine restriction decreases mitochondrial oxygen radical generation and leak as well as oxidative damage to mitochondrial DNA and proteins

Previous studies have consistently shown that caloric restriction (CR) decreases mitochondrial reactive oxygen species (ROS) (mitROS) generation and oxidative damage to mtDNA and mitochondrial proteins, and increases maximum longevity, although the mechanisms responsible for this are unknown. We recently found that protein restriction (PR) also produces these changes independent of energy restriction. Various facts link methionine to aging, and methionine restriction (MetR) without energy restriction increases, like CR, maximum longevity. We have thus hypothesized that MetR is responsible for the decrease in mitROS generation and oxidative stress in PR and CR. In this investigation we subjected male rats to exactly the same dietary protocol of MetR that is known to increase their longevity. We have found, for the first time, that MetR profoundly decreases mitROS production, decreases oxidative damage to mtDNA, lowers membrane unsaturation, and decreases all five markers of protein oxidation measured in rat heart and liver mitochondria. The concentration of complexes I and IV also decreases in MetR. The decrease in mitROS generation occurs in complexes I and III in liver and in complex I in heart mitochondria, and is due to an increase in efficiency of the respiratory chain in avoiding electron leak to oxygen. These changes are strikingly similar to those observed in CR and PR, suggesting that the decrease in methionine ingestion is responsible for the decrease in mitochondrial ROS production and oxidative stress, and possibly part of the decrease in aging rate, occurring during caloric restriction. —Sanz, A. , Caro, P., Ayala, V. , Portero‐Otin, M. , Pamplona, R. , Barja, G. Methionine restriction decreases mitochondrial oxygen radical generation and leak as well as oxidative damage to mitochondrial DNA and proteins. FASEB J. 20, 1064–1073 (2006)
On balancing market design

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