Miracle-dz/UniFAR-FTUs huggingface dataset:
Does in leadership strategies influence public sectors' KM readiness in terms of SECI processes?

The aim of this study is to investigate two different leadership strategies that contribute to knowledge management (KM) readiness in Malaysian public sector. Grounding on Nonaka and Takeuchi’s knowledge creation theory, this study defines intention to be involved in knowledge management in terms of socialization, externalization, combination, and internalization (SECI) processes. A total of 212 questionnaires are accepted for data analysis from top managers, deputy directors, assistant directors, and executives of public sectors. Partial least squares-structural equation modeling (PLS-SEM) approach is used for assessing measurement and structural models. The findings suggest that transformational leadership strategy positively influences intention to be involved in KM processes. Interestingly transactional leadership strategy is associated with intention to be involved in KM processes, except internalization process. The findings imply that there should be a trade-off between transformational and transactional leadership amongst public sectors in Malaysia, proposing ambidexterity in leadership strategies. Finally, considering the demographic factors as a categorical moderating variable, applying PLS-Multi group analysis, this study finds that the intention to be involved in KM processes differ amongst employees with distinct age and year-of-experience. Implications, contributions, and limitations are discussed.
Monthly hemostatic factor variability in women and men

Background— Hormonal status influences hemostatic factors including fibrinogen, factor VII and plasminogen activator inhibitor (PAI-1), and concentrations differ among men, premenopausal and postmenopausal women. This study examines how phases of the menstrual cycle influence variability of fibrinogen, factor VII and PAI-1. Design— We studied 103 subjects (39 premenopausal women, 18 postmenopausal women, and 46 men) during three, randomized, 8-week energy and nutrient-controlled experimental diets in the DELTA (Dietary Effects on Lipids and Thrombotic Activity) Study. Fasting blood samples were collected weekly during the last four weeks of each diet period and hemostatic factors were quantified. Two linear mixed-effects models were used for fibrinogen, factor VII and PAI-1: one to estimate and compare group-specific components of variance, the other to estimate additional fixed effects representing cyclical functions of day of menstrual cycle in premenopausal women. Results— Systematic cyclical variation with day of menstrual cycle was observed for fibrinogen (p<0.0001), factor VII (p=0.0012), and PAI-1 (p=0.0024) in premenopausal women. However, the amplitude of cycling was small relative to the total magnitude of intra-individual variability. In addition, the intra-individual variance and corresponding coefficient of variation observed in premenopausal women did not differ from postmenopausal women and men. Conclusions— The variability in hemostatic factors in premenopausal women is no greater than for postmenopausal women or men. Consequently, premenopausal women can be included in studies investigating hemostatic factor responses without controlling for stage of menstrual cycle.
From summative to developmental Incorporating design-thinking into evaluations of complex interventions

Purpose – Models of integrated care are prime examples of complex interventions, incorporating multiple interacting components that work through varying mechanisms to impact numerous outcomes. The purpose of this paper is to explore summative, process and developmental approaches to evaluating complex interventions to determine how to best test this mess. Design/methodology/approach – This viewpoint draws on the evaluation and complex intervention literatures to describe the advantages and disadvantages of different methods. The evaluation of the electronic patient reported outcomes (ePRO) mobile application and portal system is presented as an example of how to evaluate complex interventions with critical lessons learned from this ongoing study. Findings – Although favored in the literature, summative and process evaluations rest on two problematic assumptions: it is possible to clearly identify stable mechanisms of action; and intervention fidelity can be maximized in order to control for contextual influences. Complex interventions continually adapt to local contexts, making stability and fidelity unlikely. Developmental evaluation, which is more conceptually aligned with service-design thinking, moves beyond these assumptions, emphasizing supportive adaptation to ensure meaningful adoption. Research limitations/implications – Blended approaches that incorporate service-design thinking and rely more heavily on developmental strategies are essential for complex interventions. To maximize the benefit of this approach, three guiding principles are suggested: stress pragmatism over stringency; adopt an implementation lens; and use multi-disciplinary teams to run studies. Originality/value – This viewpoint offers novel thinking on the debate around appropriate evaluation methodologies to be applied to complex interventions like models of integrated care.
Fundamentals of Gas Micropattern Detectors

We performed a new series of systematic studies of gain and rate characteristics of several micropattern gaseous detectors. Extending earlier studies, these measurements were done at various pressures, gas mixtures, at a wide range of primary charges and also when the whole area of the detectors was irradiated with a high intensity x-ray beam. Several new effects were discovered, common to all tested detectors, which define fundamental limits of operation. The results of these studies allow us to identify several concrete ways of improving the performance of micropattern detectors and to suggest that in some applications RPCs may constitute a valid alternative. Being protected from damaging discharges by the resistive electrodes, these detectors feature high gain, high rate capability (10^5 Hz/mm^2), good position resolution (better than 30 micrometer) and excellent timing (50 ps sigma).
Forging Effective Strategies to Combat Iron Deﬁciency Iron Supplements: Scientiﬁc Issues Concerning Efﬁcacy and Implications for Research and Programs 1,2

Iron supplementation remains an important strategy for the prevention and treatment of iron deﬁciency anemia and can produce substantial improvements in the functional performance of iron deﬁcient individuals and populations. Many potential beneﬁts of iron supplementation require further exploration, including its effect on vitamin A and iodine metabolism. There is strong evidence that vitamin A and riboﬂavin deﬁciencies affect iron utilization from supplements and are important on a global scale, but little evidence that folate and vitamin B-12 deﬁciencies play a major causal role in the global burden of anemia. The efﬁcacy of multiple micronutrient supplements for the prevention and treatment of anemia must be further evaluated. Because weekly supplementation with iron is effective at improving iron status, this option should be thoroughly explored and evaluated in the context of programs for the prevention and the treatment of iron deﬁciency and anemia. More conformation is warranted concerning the number of tablets that must be consumed in different situations, and the efﬁcacy of supplying other micronutrients weekly with iron. Weekly supplementation programs may improve the logistical and economic constraints that currently limit the provision of supplements to the many target population groups for whom they are recommended, but usually fail to reach. Further work is required to clarify the purpose, delivery and outcomes of iron supplementation programs. J. Nutr. 132: 813S–819S, 2002.
Kinematic and Dynamic Analysis and Simulation of Complex Mechanisms Using the MATLAB Software

The research presented in this paper is related to the development of complex mechanisms using virtual models obtained by integration various modern computer programs, specialized in certain fields of computer science. The industrial robots, as a typical representative of complex mechanisms with six degrees of freedom, carried out the definition, analysis and simulation for the considered mechanism. Virtual model with a control algorithm implemented in the MATLAB, as an open kinematic chain. This software solves the problem with difficult matrix algebra and by using the add-on Robotics Toolbox can be made behavioural simulation, and verification for the model which provides analysis of the behaviour for real robots. In this case we use industrial robot FANUC S-430iF, where we wrote up the whole process for solving kinematics and dynamics for complex mechanisms by using computers, from the formation of the transformation matrix through solving direct and inverse kinematics and dynamics, as well as movement simulation. To define the 3D model was used SolidWorks.
Generating Semantic Frames from Queries Using Natural Language Query Processing In Concertize Search Engine

Question and Answering (QA) frameworks are alluded as virtual associates and are imagined to be the cutting edge call focus. However the precision of such QA frameworks isn't as attractive and necessities critical upgrade. Understanding the goal of the inquiry is a critical supporter of an effective framework which has not been frequently broke down. To answer English dialect questions utilizing PC is an intriguing and testing issue. For the most part such issues are dealt with under two classifications: open Domain issues and close space issues. This paper exhibits a framework that endeavours to explain both close and open area issues. Answers to inquiries from close area can't be looked utilizing a web index. Henceforth answers must be put away in a database by an area master. At that point, the test is to comprehend the English dialect question with the goal that the arrangement could be coordinated to the separate answer in the database. We utilize a format coordinating method to play out this coordinating. The framework is produced with the end goal that the inquiries can be asked utilizing short messages from a cell phone and accordingly the framework is intended to comprehend SMS dialect notwithstanding English.
A photometric study of 21 Comae Berenices.

New photometric (B and V) observations of the Ap star 21 Com were obtained at the Kitt Peak and the David Dunlap Observatories. The observations confirmed the 30-minute light variation reported in 1957 by Bahner and Mawridis. The range in V varied from 0.004 to 0.01gm and the range in (B -- V) was very small. The cause of the variation was probably pulsation; this conclusion is based on the similarity between the propenties of 21 Com and the corresponding properties of known sigma Sct stars, such as Tnumpler 51 in the Pleiades. If this conclusion is correct, then the Ap and Am stars differ in that at least one Ap star pulsates whereas no Am star pulsates. The implications of this difference are discussed briefly. The observations also confirmed the longer- period light variation (period, about a day; range about 0.02m in B and V) noted previously. New photometric observations of two other Ap stars (41 Tau and Hd 32633) showed no evidence for short-period light variations. (auth)
SHAPE Project Vision-e: Deep Tile Inspection

Vision-e is an Italian company focused on machine vision application. One of the main market is the ceramic tile where inspection system is used to automatically check the quality of the product. The fourth industry revolution tends to create factories with few human controllers and need automatic systems without configuration or supervision. This project goes in that direction trying to increase the performance of actual machine vision systems we created, in particular the clustering phase that is crucial for a good inspection. We investigated Deep Learning technologies applied to clustering tiles using the DeepCluster approach and the good results we get, show us that this is the right way to reach the goal and to continue, starting from a study on the choice of input data.
Algorithms for increasing the efficiency and fidelity of fluid simulations

This dissertation presents algorithms for the simulation of fluids. Realistic simulations of smoke, water and fire are amongst the most desired in the special effects industry. These phenomena often contain complex motions and rich visual details that are difficult or impossible to animate by hand. These phenomena are also extremely costly to simulate using current technology. The first part of this thesis will focus on increasing the efficiency of these simulations. In order to optimize the use of computational resources, we present an adaptive octree mesh or a level of detail approach where more grid cells are placed in visually interesting regions. The enabling technology for this approach is a new technique for discretizing the Poisson equation on an unrestricted octree grid. We will conclude this section by demonstrating the flexibility of the algorithm by several examples. The rest of the thesis will focus on simulating new phenomena. We will describe a novel technique for melting and burning solid materials including the simulation of the resulting liquid and gas. Our method allows for state of the art techniques to be used for both the solid and the fluid without compromising simulation quality when coupling them together or converting one into the other. In addition, an approach to extend the particle level set method to the simulation of an arbitrary number of regions is presented. Using a separate particle level set method for each region, we present a novel projection algorithm that can be used to provide a dictionary that translates between the vector of level set values and the standard single-valued level set representation. This dictionary allows the standard level set techniques to be used without any additional special treatment.
Alignment of genomic sequences with intrinsic disorder and tandem repeats

A prerequisite to most evolutionary analyses is a reliable prediction of homologous relationships in a given set of genomic sequences. Homologous genes or characters can be predicted computationally by either pairwise or multiple sequence alignment algorithms based on statistical models of sequence evolution. Although alignment methods have been being developed for multiple decades, for certain sequence features still improved algorithms are required. Here, we focus on new models and algorithms for sequences with intrinsic disorder and tandem repeats, which have been rarely dealt with explicitly in sequence alignment although they are present in > 30% of eukaryotic proteins. Although intrinsically disordered protein regions (IDRs) do not have a well-defined tertiary structure, proteins with IDRs perform a multitude of functions, often relying on native disorder to achieve the necessary binding flexibility and strength. IDRs are frequently found in all three kingdoms of life, and may occur in short stretches or span whole proteins. IDRs are difficult to align as they usually evolve faster and have a biased amino acid composition. We build a database of homologous sequences containing intrinsic disorder and estimate a Markov model of amino acid evolution separately for ordered and disordered regions. This model can be used in e.g. sequence alignment and phylogenetic reconstruction and it gives insights into the evolution of IDRs, contrasting patterns specific to ordered protein regions and the corresponding IDRs. As an alternative to the DO model we evaluate the performance of context-specific profiles, a method originally proposed for pairwise homology detection, and extend its definition to multiple sequence alignment. As a result the multiple alignment of sequences with IDRs is improved with only linear time complexity with respect to sequence length. Tandem repeats (TRs) are often present in proteins with crucial functions, responsible for resistance, pathogenicity, and associated with infectious or neurodegenerative diseases. This motivates numerous studies of TRs and their evolution, requiring accurate multiple sequence alignment. We develop a multiple sequence alignment algorithm which takes into account that TR units may be lost or inserted at any position of a TR region by replication slippage or recombination. By explicitly modeling and reconstructing these events we improve alignment quality and are able to study TR evolution e.g. by estimating TR indel frequencies in different clades of a phylogeny. The algorithm is implemented in a graph-based multiple sequence alignment framework, which produces phylogenetically sensible gap patterns while maintaining robustness by allowing alternative splicings and errors in the branching pattern of the guide tree. Overall, this thesis contributes to faster and more accurate alignments of sequences with intrinsic disorder and tandem repeats, as we demonstrate on real as well as simulated data.
The digital patient: machine learning techniques for analyzing electronic health record data

The current unprecedented rate of digitization of longitudinal health data — continuous device monitoring data, laboratory measurements, medication orders, treatment reports, reports of physician assessments — allows visibility into patient health at increasing levels of detail. A clearer lens into this data could help improve decision making both for individual physicians on the front lines of care, and for policy makers setting national direction. However, this type of data is high-dimensional (an infant with no prior clinical history can have more than 1000 different measurements in the ICU), highly unstructured (the measurements occur irregularly, and different numbers and types of measurements are taken for different patients) and heterogeneous (from ultrasound assessments to lab tests to continuous monitor data). Furthermore, the data is often sparse, systematically not present, and the underlying system is non-stationary. Extracting the full value of the existing data requires novel approaches. In this thesis, we develop novel methods to show how longitudinal health data contained in Electronic Health Records (EHRs) can be harnessed for making novel clinical discoveries. For this, one requires access to patient outcome data — which patient has which complications. We present a method for automated extraction of patient outcomes from EHR data; our method shows how natural languages cues from the physicians notes can be combined with clinical events that occur during a patient’s length of stay in the hospital to extract significantly higher quality annotations than previous state-of-the-art systems. We develop novel methods for exploratory analysis and structure discovery in bedside monitor data. This data forms the bulk of the data collected on any patient yet, it is not utilized in any substantive way post collection. We present methods to discover recurring shape and dynamic signatures in this data. While we primarily focus on clinical time series, our methods also generalize to other continuous-valued time series data.
Reasoning Techniques in DatalogMTL

DatalogMTL is a recently introduced extension of Datalog with operators from metric temporal logic (MTL). It allows for performing complex temporal reasoning tasks over the rational timeline, which makes it suitable for many practical applications. Although the main reasoning tasks in DatalogMTL are decidable, they have high computational complexity, and so, developing practically efficient reasoning techniques is challenging. Consequently, a number of approaches have been recently established; some of them have already been implemented and tested experimentally, but no comparison of these techniques has been provided yet. To fill this gap, we present an overview of reasoning techniques in DatalogMTL, sketch relations between them, and discuss their properties. Moreover, we present our ongoing research in this area and possible future directions thereof.
Electron Scattering Theory for Ordered and Disordered Matter

Introduction Local density functional theories Schrodinger and Dirac Hamiltonians for a central field Resolvents and Green functions Single-site scattering Multiple scattering Multiple scattering theory for disordered systems - the coherent potential approximation Spectral densities Some illustrations Charge self-consistency and total energies Applications of multiple scattering I: band structure spectroscopy Applications of multiple scattering II: physical and transport properties related to the Fermi energy Applications of multiple scattering III: ferromagnetic alloys and finite temperature magnetism
Wavelets in Econometrics: An Application to Outlier Testing

In recent years, wavelets have become widely used in physics, engineering, and mathematics. They have been used for signal processing, image processing, numerical computation, and data compression. Wavelets have not, however, been used very much in the fields of Economics, Econometrics, and Finance. In this study, We will look at the wavelet transform in the context of multiresolution analysis, discuss its uses in other fields, and present an Econometric application of wavelets to outlier detection.
Modelling rigid line and Dirichlet boundary conditions with arbitrary geometry by intrinsic XFEM

The most difficult aspect of modelling discontinuity on complicated domains is the mesh. In the extended finite element method (XFEM), the FE mesh need not conform to the internal boundaries. In the intrinsic XFEM, no additional unknowns are introduced at the nodes. Some of these discontinuities such as cracks, voids were developed in earlier papers. In the current work, the FE mesh is allowed to be independent of the rigid line (fixed DOFs path). Copyright © 2013 John Wiley & Sons, Ltd.
Named Entity Recognition for LivingNER-Species based on BERT and Span Detection

Recently, organisms/species have been attracted to NLP studies, especially for non-English content. So, we need high-quality guidelines and corpora to determine where species or humans are in medical text. Task 1 of LivingNER (Species mention entity recognition) gives a plain text clinical case report document collection, participants must return the exact character offsets of all species mentions, both human and non-human. So, this paper tries to figure out a satisfactory way by using a model based on BERT and span detection.