Miracle-dz/UniFAR-FTUs huggingface dataset:
Aalborg Universitet A 3 D thermal network model for monitoring imbalanced thermal distribution of press-pack IGBT modules in MMC-HVDC applications

In this paper, the impact of a double-sided press-pack insulated-gate-bipolar-transistor (PP IGBT) cooling structure on its thermal impedance distribution is studied and explored. A matrix thermal impedance network model is built by considering the multi-chip thermal coupling effect for the collector side of the PP IGBT. Moreover, a verification has been made by comparing the proposed matrix thermal network model and the conventional lumped RC network model provided by the manufacturer. It is concluded that the collector side has lower thermal resistance and dissipates about 88% of the heat generated by the IGBT chips inside the module. Then, a modular-multilevel-converter high-voltage-direct-current (MMC-HVDC)-based type test setup composed of the press-pack IGBT stacks is established and the junction temperature is calculated with the proposed thermal model and verified by temperature measurements.
A Survey of Architectural Design Decision Models and Tools

In the field of software architecture, there has been a paradigm shift from describing the outcome of architecting process mostly described by component and connector (know-what) to documenting architectural design decisions and their rationale (know-how) which leads to the production of an architecture. This paradigm shift results in emergence of various models and related tools for capturing, managing and sharing architectural design decisions and their rationale explicitly. This report intends to make a survey about the well-known existing architectural design decision models and their related tools
Boosting a weak learning algorithm by majority pdf

Proposed running head: Boosting by majority. Access to a weak learning algorithm, can generate hypotheses of arbitrary accuracy. Boosting a weak learning algorithm by majority. To be published in Information and Computation. We present an algorithm for improving the accuracy of algorithms for learning binary concepts. The improvement is achieved by combining a. The boosting algorithm calls this weak or base learning algorithm. For combining the weak rules, simply taking a weighted majority vote of.Boosting is a machine learning ensemble meta-algorithm for reducing bias primarily and also. And a family of machine learning algorithms which convert weak learners to strong ones. The weight of repeatedly misclassified examples, e.g, boost by majority and BrownBoost. The Strength of Weak Learnability PDF.PDF File 25 KB.
Shoot and root culture of Hypericum perforatum L . transformed with Agrobacterium rhizogenes A 4 M 70

Hairy root cultures of Hypericum perforatum were obtained following inoculation of aseptically germinated seedlings with A. rhizogenes strain A4M70GUS. Effect of sucrose on the growth and biomass production of hairy root cultures was investigated. Hairy root cultures spontaneously regenerated shoots buds from which a number of shoot culture clones was established. Transformed shoot cultures exhibited good shoot multiplication, elongation and rooting on a hormone-free woody plant medium. Plants regenerated from hairy roots were similar in appearance to the normal, nontransformed plants. Additional key words: GUS activity, hairy roots, shoot regeneration, St. John's wort, sucrose.
RIT Scholar Works RIT Scholar Works

Diﬀusion Tensor Imaging is a type of Magnetic Resonance Imaging that allows for the examination of brain connectivity and axonal integrity. Diﬀusion Tensor Images are created by capturing Diﬀusion-Weighted MRI images with speciﬁc RF pulses, inputing the images and the RF pulse gradient vectors into a set of equations, and solving the equations with linear algebra. To compare one DTI image with another, the images can be aligned using Image Registration. Image Registration works by deﬁning a metric that describes the similarity between two images and iteratively transforming one of the images until the similarity measure is minimized. Existing methods of DTI comparison ﬁt tensors to DW-MRI images, compute matrix logarithms to transform the tensors into a vector-space, register the vector-space structures, and then matrix exponentiate the results to transform them back to tensors. Logging and exponentiating the tensors introduces biases and noise so this registration framework is not ideal. Additionally, the information encoded in a diﬀusion tensor is a subset of the information present in the original DW-MRI images. This thesis proposes a new registration framework which avoids these shortcomings by registering the underlying DW-MRI images and then ﬁtting the diﬀusion tensors to the registered DW-MRI images and transformed gradient vectors. The existing DTI registration framework and the new DW-MRI registration framework are applied to a small image set and their results are compared along a number of qualitative and quantitative attributes.
Exploring the factors affecting the motivation for learning from the perspective of public health students: A qualitative study

Objective. Despite the significant role of motivation in achieving success among public health students, students often do not demonstrate adequate motivation for learning and education. This study was performed to determine factors affecting the motivation for learning from the perspective of public health students via content analysis approach. Methods. This qualitative study was conducted at Kurdistan University of Medical Sciences in Sanandaj, Iran in 2017. 15 students were included in the study by using purposive sampling. Data were collected through personal interviews, group discussions, and field notes, and they were analyzed through conventional content analysis. Several parameters were taken into account to support the accuracy and the strength of the data: acceptability, confirmability, and transferability. Results. Five categories were derived from the data analysis, including “University Policy”, “Health Status”, “Teacher’s Role”, “Student-Related Factors” and “University Facilities”. Attention to the health status and its priority in the opinion of people, authorities, and educational system were the most important factors involved in the students’ motivation for learning. Conclusions. To increase motivation for learning, students have diverse needs that should be met. Attention to the components of motivation for learning not only enhances academic achievement but also promotes the formation of health behaviors in the society.
Osteotome Sinus Floor Elevation without Grafting : A 10-Year Study of Cone-Beam Computerized Tomography versus Periapical X-Rays

Clinical Director, Swiss Dental Clinics Group, Ardentis Clinique Dentaire Lausanne, Lausanne, Switzerland. Senior Scientist, Swiss Dental Clinics Group, Ardentis Clinique Dentaire Vevey, Vevey, Switzerland. Clinical Director, Swiss Dental Clinics Group, Ardentis Clinique Dentaire Genève, Geneva, Switzerland. Clinical Director, Swiss Dental Clinics Group, Ardentis Clinique Dentaire Lausanne, Lausanne, Switzerland. Clinical Director, Swiss Dental Clinics Group, Ardentis Clinique Dentaire Vevey, Vevey, Switzerland.
uRNN : An Approach to Bounded Gradients

Vanishing and exploding gradients have persistently plagued vanilla recurrent neural networks (RNNs). To rectify these problems, unitary recurrent networks (uRNNs), which restrict recurrent weight matrices to the space of unitary matrices, have been suggested due to theoretical bounds on their gradient norms. We prove certain additional bounds related to gradients norms and implement various forms of uRNNs. Our models exhibit signs of “long-term memory” on both a concocted pathological task and language modelling. Our mentor is Michael Hahn. 1 Background and Related Work The phenomena of vanishing and exploding gradients are closely tied to the eigenvalues of the recurrent weight matrix Wrec in a RNN. Pascanu et al. [2012] suggests, denoting λ1 as the largest magnitiude of the eigenvalues of Wrec, that λ1 < 1 γ is a sufficient condition for vanishing gradients and that λ1 > 1 γ is a necessary condition for exploding gradients, where γ is the upper bound on the magnitude of derivative σ′ of the activation function used in the RNN. Letting xt be the hidden state at time t, they observe that
INFLUENCE OF VERTICAL INTEGRATION STRATEGY ON PERFORMANCE OF NON-FINANCIAL FIRMS LISTED AT THE NAIROBI SECURITIES EXCHANGE , KENYA Videlis

The choice of firms’ diversification strategies and their performance has been the centre of attention in the strategy and finance fields both empirically and theoretically. However in general, previous studies have analysed the integration–performance relationship without differentiating the firms into financial and non-financial sectors, but rather the samples were pooled from both sectors. The aim of this study is to investigate the influence of vertical integration strategy on performance of non-financial firms listed at the Nairobi Securities Exchange. The study used descriptive correlational survey design. Target population was all 45 listed non-financial firms. Primary and secondary data were required; primary data was collected using a semi-structured questionnaire and audited financial reports of the firms were used to collect secondary data. Through descriptive, correlation and regression analyses, the study findings revealed that there was a significant positive relationship between vertical integration and firm performance. Regression analysis revealed that 19.5% of changes in firm performance were attributed to the use of vertical integration strategy. This study concluded that vertical integration is an essential strategy for use by firms in their quest to lower transaction costs, increase market power and improve on firm’s technical efficiencies. The study recommended that management of firms that are yet to adopt this strategy should put in place an internal organizational policy and culture to encourage its adoption. Managers should also create initiative in their firms with regard to vertical integration which should consider vertical integration issues as part of their performance review.
J an 2 01 4 ACFI-T 1303 Magnetic Fields in an Expanding Universe

We find a solution to 4D Einstein-Maxwell theory coupled to a massless dilaton field describing a Melvin magnetic field in an expanding universe with ‘stiff matter’ equation of state parameter w = +1. As the universe expands, magnetic flux becomes more concentrated around the symmetry axis for dilaton coupling a < 1/ √ 3 and more dispersed for a > 1/ √ 3. An electric field circulates around the symmetry axis in the direction determined by Lenz’s law. For a = 0 the magnetic flux through a disk of fixed comoving radius is proportional to the proper area of the disk. This result disagrees with the usual expectation based on a test magnetic field that this flux should be constant, and we show why this difference arises. We also find a Melvin solution in an accelerating universe with w = −7/9 for a dilaton field with a certain exponential potential. Our main tools are simple manipulations in 5D Kaluza-Klein theory and related solution generating techniques. We also discuss a number of directions for possible extensions of this work. kastor@physics.umass. edu traschen@physics.umass. edu
Design and Optimization of a Large-Scale Permanent Magnet Synchronous Generator

Direct drive permanent magnet synchronous generators have numerous advantages such as improved reliability, low maintenance, long life, and developed performance characteristics. Focus of this paper is on the development of a step-by-step method for the design of a permanent magnet synchronous generator. Then the winding function method is used to model the generator and to analytically calculate its output characteristics. The analytical results of the designed generator are evaluated with the finite element analysis (FEA) results and it is demonstrated that the achieved results from both methods are well matched with the experimental measurements of the Northern Power direct-drive generator. The sensitivity analysis and the optimization based on the genetic algorithm are used to achieve an optimum generator. The optimization goal is obtaining higher efficiency and power factor with lower required permanent magnet (PM) volume and voltage regulation for the optimum machine compared to the initial design. In addition, the calculation of the voltage total harmonic distortion (THD) is presented and the optimum skew angle for the optimum generator is computed to reduce the voltage THD.
Self-efcaca and qualita of work life : studa with militara state police ofcers

The present study aims to identify the relationship between quality of work life and general self-efficacy beliefs in the Military Police of the Federal District. The research is set up as a case study, with correlational design and quantitative approach. We used the Inventory of Assessment of Quality Work Life and General Self-Efficacy Scale. The participants were 1027 police officers, including 895 men and 114 women, with an average time of 16 years of service. The results showed that there are no strong significant correlations between QWL and self-efficacy. It follows that it cannot promote QVT focusing only on the individual, because even the participants realizing effective self, did not result in a positive perception of QWL.
On Increasing Design Reliability in Advanced Manufacturing Technology

This report is to present some results of the project funded by National Science Council in 2008 school year. Our objectives in this final year are to continue to explore and find new techniques in increasing circuit reliability due to advanced technology manufacturing variations. As the technology scales down to nanometer, the yield degradation caused by inter-die variations is getting worse. Using adaptive body bias is an effective method to mitigate the yield degradation (especially for memory compiler generated SRAMs), however we need to know a die having high threshold voltage or low threshold voltage (also called process corner) in order to use this technique. Unfortunately, it is hard to detect the process corners when PMOS and NMOS variations are uncorrelated. In this project, we propose some improved circuits of delay monitor and leakage monitor for both PMOS and NMOS process corner detection, which are uncorrelated in inter-die variations. The experimental results show that our circuits can clearly distinguish each process corner of PMOS and NMOS, thus improve the yield by adopting correct body bias. This report is from the publication of MTDT 2009.
O ct 2 01 9 Subspace Estimation from Unbalanced and Incomplete Data Matrices : l 2 , ∞ Statistical Guarantees

This paper is concerned with estimating the column space of an unknown low-rank matrix A ∈ R d1×d2 , given noisy and partial observations of its entries. There is no shortage of scenarios where the observations — while being too noisy to support faithful recovery of the entire matrix — still convey sufficient information to enable reliable estimation of the column space of interest. This is particularly evident and crucial for the highly unbalanced case where the column dimension d2 far exceeds the row dimension d1, which is the focal point of the current paper. We investigate an efficient spectral method, which operates upon the sample Gram matrix with diagonal deletion. We establish statistical guarantees for this method in terms of both l2 and l2,∞ estimation accuracy, which improve upon prior results if d2 is substantially larger than d1. To illustrate the effectiveness of our findings, we develop consequences of our general theory for three applications of practical importance: (1) tensor completion from noisy data, (2) covariance estimation with missing data, and (3) community recovery in bipartite graphs. Our theory leads to improved performance guarantees for all three cases.
dem Repeats Dictate the kmoth Chorion , a Natural oid s † and Vassiliki

Silkmoth chorion is a fibrous structure composed mainly of two major protein classes, families A and B. Both families of silkmoth chorion proteins present a highly conserved, in sequence and in length, central domain, consisting of Gly-rich tandem hexapeptide repetitive segments, flanked by two more variable N-terminal and C-terminal arms. Primary studies identified silkmoth chorion as a functional protective amyloid by unveiling the amyloidogenic properties of the central domain of both protein families. In this work, we attempt to detect the principal source of amyloidogenicity of the central domain by focusing on the role of the tandem hexapeptide sequence repeats. Concurrently, we discuss a possible mechanism for the self-assembly of class A protofilaments, suggesting that the aggregation-prone hexapeptide building blocks may fold into a triangle-shaped β-helical structure. © 2018 Elsevier Ltd. All rights reserved.
WALKING RESTORES THE REPRODUCTIVE FUNCTION OF FEMALE RATS FROM REDUCED LITTERS , A CLASSICAL MODEL OF OBESIT Y

As physical activity is a significant aid against obesity and its complications, this work was planned to assess the consequences of litter size reduction, a classical model of obesity, and treadmill walking on the reproductive function of adult female rats. Female rats were raised in reduced (three puppies, NR) or conventional (nine puppies, NC) litters during lactation, with free supply of chow after weaning. Some of the rats of each group were not exercised (sedentary, S) while some were subjected to treadmill walking (exercised, E). Litter size reduction increased biometric parameters (body weight, Lee index, weight/length ratio and adiposity) significantly (p<0.05, twoway ANOVA). Only one regular estrous cycle, a high number of cystic follicles (28) and irregular ovarian morphology were recorded in the sedentary rats (NR-S). These rats, when mated, did not procreate. Treadmill walking had a significant effect on most of the biometric parameters (p<0.05, two-way ANOVA). The exercised female rats (NR-E) had reproductive function similar to those of the NC groups: 14 regular estrous cycles, 16 puppies, and 16 cystic follicles. In the reduced-litter female rats, walking since early life preserved estrous rhythmicity and fertility, which were impaired in the sedentary reduced-litter females.
The Common Information for N Dependent Random Variables

This paper generalizes Wyner’s definition of common information of a pair or random variables to that of N random variables. We prove coding theorems that show the same operational meanings for the common information of two random variables generalize to that of N random variables. As a byproduct of our proof, we show that the Gray-Wyner source coding network can be generalized to N source sequences with N decoders. We also establish a monotone property of Wyner’s common information which is in contrast to other notions of the common information, specifically Shannon’s mutual information and Gács and Körner’s common randomness. Examples about the computation of Wyner’s common information of N random variables are also given.
Scotland ' s Rural College The influence of neonatal environment on piglet play behaviour and post-weaning social and cognitive development

22 Research has shown that the domestic pig is highly playful throughout its development and that play is 23 an important aspect of social and cognitive development. Therefore the neonatal environment is 24 fundamental to successful stimulation of play in neonatal pigs, which could have indirect and direct 25 socio-cognitive effects on pigs post-weaning and therefore influence social interactions known to cause 26 welfare concerns (e.g. aggression during mixing). This study investigated how play preand post27 weaning developed in two neonatal environments (NE); the conventional farrowing crate (NEC) and a 28 more environmentally complex alternative PigSAFE pen (NEP) and to discover whether this had an effect 29 on piglet’ cognitive abilities in Spontaneous Object Recognition Tests for two retention times (15 and 60 30 minutes) post-weaning. Hourly focal sampling was used to record play behaviours preand post31 weaning in 72 piglets of mixed sex (36 per NE) from a total population of 117 piglets from 12 litters. Out 32 of the 72 piglets, 24 were used in the cognitive Spontaneous Object Recognition tests five weeks post33 weaning. Linear mixed models showed that NEP piglets displayed play behaviours quicker after birth 34 than NEC piglets: locomotor (F = 7.62(1,11), P = 0.020); sow interaction (F = 5.27(1,11), P = 0.045); and social 35 interaction (F = 23.61(1,11), P < 0.001). NEP piglets played more pre-weaning than NEC piglets (F = 36 5.06(1,71), P = 0.051) and despite initial higher levels of aggression at weaning, displayed less chronic 37 aggression post-weaning as indicated by lesion scores of all piglets (F = 27.05(1,116), P < 0.001). NE was 38 shown to have a significant effect on the 15 minute cognitive retention test; with NEP piglets spending 39 more time interacting with the novel object than the familiar, compared to NEC piglets (F = 5.39(1,23), P = 40 0.045). There was no NE effect for the 60 minute retention test. It was concluded that play is 41 fundamental to successful socio-cognitive development (e.g. aggressive conflicts) and relates to play 42 function theories of training for the unexpected. Its effect on play behaviours are short-term and highly 43
The EU , Regional Conflicts and the Promotion of Regional Integration : Setting The Framework of Analysis 1

Over the past two decades, regional conflicts have increasingly shaped the security discourse. While during the Cold War one global conflict prevailed, and interfered with regional disputes as an overlay, the post-Cold War era has been characterized by a bottom-up dynamic, whereby regional conflicts have started translating into global tensions (Buzan and Wæver 2003). By drawing in a wide range of actors across state boundaries, regional conflicts bear the risk of spill-over effects, and hence represent global challenges that require our attention. Indeed, the European Security Strategy (2003) defines regional conflicts as global security challenges that ‘impact on European interests directly and indirectly’ (p. 4).
Mild Cognitive Impairment (MCI) is a heterogeneous condition between normal aging and dementia. Upon neuropsychological testing, MCI can be divided into four groups: single- domain amnestic MCI (sd-aMCI), multiple-domain amnestic MCI (md-aMCI), single- and multiple-domain non-amnestic MCI (sd-naMCI,

Mild Cognitive Impairment (MCI) is a heterogeneous condition between normal aging and dementia. Upon neuropsychological testing, MCI can be divided into four groups: singledomain amnestic MCI (sd-aMCI), multiple-domain amnestic MCI (md-aMCI), singleand multiple-domain non-amnestic MCI (sd-naMCI, md-naMCI). Some controversy exists about whether the risk of progression to Alzheimer's disease (risk-AD) is increased in all MCI subtypes. We meta-analyzed the risk-AD for four MCI groups using random-effects metaregression with the Hierarchical Robust Variance Estimator and sample size, criterion for objective cognitive impairment, length of follow-up and source of recruitment as covariates. From a pool of 134 available studies, 81 groups from 33 studies (N = 4,907) were metaanalyzed. All the studies were rated as having a high risk of bias. aMCI is overrepresented in studies from memory clinics. Multivariate analyses showed that md-aMCI had a similar riskAD relative to sd-aMCI, whereas both sd-naMCI and md-naMCI showed a lower risk-AD compared to sd-aMCI. The risk-AD was significantly associated with differences in sample sizes across studies and between groups within studies. md-aMCI had a similar risk-AD relative to sd-aMCI in studies from memory clinics and in studies in the community. Several potential sources of bias such as blindness of AD diagnosis, the MCI diagnosis approach and the reporting of demographics were associated with the risk-AD. This work provides important data for use in both clinical and research scenarios.