Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge, economic organization and property rights : selected papers

Contents: IntroductionPART I: KNOWLEDGE AND MICRO FOUNDATIONS1. Nicolai J. Foss (1996), 'Knowledge-based Approaches to the Theory of the Firm: Some Critical Comments'2. Nicolai J. Foss (2003), 'Bounded Rationality and Tacit Knowledge in the Organizational Capabilities Approach: An Assessment and a re-Evaluation'3. Teppo Felin and Nicolai J. Foss (2005), 'Strategic Organization: a Field in Search of Micro-foundations'4. Nicolai J. Foss (2003), 'The Rhetorical Dimensions of Bounded Rationality: Herbert A. Simon and Organizational Economics'5. Nicolai J. Foss and Torben Pedersen (2002), 'Transferring Knowledge in MNCs: The Role of Sources of Subsidiary Knowledge and Organizational Context'6. Nicolai J. Foss (1999), 'The Use of Knowledge in Firms'7. Kirsten Foss and Nicolai J. Foss (2000), 'Theoretical Isolation in Contract Theory: Suppressing Margins and Entrepreneurship'8. Nicolai J. Foss (2007), 'The Emerging Knowledge Governance Approach: Challenges and Characteristics'PART II: ECONOMIC ORGANIZATION9. Nicolai J. Foss (2002), 'Coase vs Hayek: Economic Organization and the Knowledge Economy'10. Nicolai J. Foss (2003), 'Selective Intervention and Internal Hybrids: Interpreting and Learning from the Rise and Decline of the Oticon Spaghetti Organization'11. Kirsten Foss, Nicolai J. Foss and Xose H. Vazquez (2006),'Tying the Manager's Hands': Constraining Opportunistic Managerial Intervention'12. Nicolai J. Foss and Keld Laursen (2005), 'Performance Pay, Delegation and Multitasking under Uncertainty and Innovativeness: An Empirical Investigation'PART III: PROPERTY RIGHTS AND ENTREPRENEURSHIP13. Kirsten Foss and Nicolai J. Foss (2001), 'Assets, Attributes and Ownership'14. Kirsten Foss and Nicolai J. Foss (2005), 'Resources and Transaction Costs: How Property Rights and Economics Furthers the Resource-Based View'15. Kirsten Foss, Nicolai J. Foss and Peter G. Klein (2007), 'Original and Deprived Judgement: An Entrepreneurial Theory of Economic Organization'16. Christian BjA rnskov and Nicolai J. Foss (2008), 'Economic Freedom and Entrepreneurial Activity: Some Cross-Country Evidence'Index
Glabridin Mediate Caspases Activation and Induces Apoptosis through JNK1/2 and p38 MAPK Pathway in Human Promyelocytic Leukemia Cells

Background Glabridin, a prenylated isoflavonoid of G. glabra L. roots, has been associated with a wide range of biological properties such as regulation of energy metabolism, estrogenic, neuroprotective, anti-osteoporotic, and skin-whitening in previous studies. However, the effect of glabridin on tumor cells metastasis has not been clearly clarified. Here, the molecular mechanism by which glabridin anticancer effects in human promyelocytic leukemia cells was investigated. Methodology and Principal Findings The results showed that glabridin significantly inhibited cell proliferation of four AML cell lines (HL-60, MV4-11, U937, and THP-1). Furthermore, glabridin induced apoptosis of HL-60 cells through caspases-3, -8, and -9 activations and PARP cleavage in dose- and time-dependent manner. Moreover, western blot analysis also showed that glabridin increase phosphorylation of ERK1/2, p38 MAPK and JNK1/2 in dose- and time-dependent manner. Inhibition of p38 MAPK and JNK1/2 by specific inhibitors significantly abolished the glabridin-induced activation of the caspase-3, -8 and -9. Conclusion Taken together, our results suggest that glabridin induced HL-60 cell apoptosis through p38 MAPK and JNK1/2 pathways and could serve as a potential additional chemotherapeutic agent for treating AML.
CAP: co-scheduling based on asymptotic profiling in CPU+GPU hybrid systems

Hybrid systems with CPU and GPU have become the new standard in high performance computing. Workloads are split into two parts and distributed to different devices to utilize both CPU and GPU for data parallelism in hybrid systems. But it is challenging for users to manually balance workload between CPU and GPU since GPU is sensitive to the scale of the problem. Therefore, current dynamic schedulers balance workload between CPU and GPU periodically and dynamically. The periodical balance operation causes frequent synchronizations between CPU and GPU and the synchronizations often degrade the overall performance. To solve the problem, we propose a Co-Scheduling Strategy Based on Asymptotic Profiling (CAP). CAP dynamically splits one task's workload to CPU and GPU and adopts the profiling technique to predict the workload in next partition. CAP is optimized for GPU's performance characteristics to balance workload between CPU and GPU with only a few synchronizations. We examine our proof-of-concept system with four benchmarks and results show that CAP produces up to 45.1% performance improvement compared with the state-of-art co-scheduling strategy.
Metabolism and Disposition of the Metabotropic Glutamate Receptor 5 Antagonist ( mGluR 5 ) Mavoglurant ( AFQ 056 ) in Healthy Subjects

The disposition and biotransformation of C-radiolabeled mavoglurant were investigated in four healthy male subjects after a single oral dose of 200 mg. Blood, plasma, urine, and feces collected over 7 days were analyzed for total radioactivity, mavoglurant was quantified in plasma by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), and metabolite profiles were generated in plasma and excreta by high-performance liquid chromatography (HPLC) and radioactivity detection. The chemical structures of mavoglurant metabolites were characterized by LC-MS/MS, wetchemical and enzymatic methods, NMR spectroscopy, and comparison with reference compounds. Mavoglurant was safe and well tolerated in this study population. Mavoglurant absorption was ‡50% of dose reaching mean plasma Cmax values of 140 ng/ml (mavoglurant) and 855 ng-eq/ml (total radioactivity) at 2.5 and 3.6 hours, respectively. Thereafter, mavoglurant and total radioactivity concentrations declined with mean apparent half-lives of 12 and 18 hours, respectively. The elimination of mavoglurant occurred predominantly by oxidative metabolism involving primarily 1) oxidation of the tolyl-methyl group to a benzyl-alcohol metabolite (M7) and subsequently to a benzoic acid metabolite (M6), and 2) oxidation of the phenyl-ring leading to a hydroxylated metabolite (M3). The subjects were mainly exposed to mavoglurant and seven main metabolites, which combined accounted for 60% of C-AUC0–72 h (area under the concentration-time curve from time 0 to infinity). The primary steps of mavoglurant metabolism observed in vivo could partially be reproduced in vitro in incubations with human liver microsomes and recombinant cytochrome P450 enzymes. After 7 days, the mean balance of total radioactivity excretion was almost complete (95.3% of dose) with 36.7% recovered in urine and 58.6%
Phase noise optimization of CMOS VCO with double-harmonic-tuned LC tank

A double-harmonic-tuned LC tank (DHT tank) is proposed for significant phase-noise suppression in CMOS voltage-controlled oscillator (VCO). The DHT tank presents open at the fundamental and third harmonic and short at the second harmonic, which ensures square-like output waveform to significantly suppress the flicker-noise up-conversion and the noise around 2ƒo. This fundamental open and the second-harmonic short effect are valid for the entire tuning range such that low phase noise can be obtained over the entire tuning range. The measured phase noise is −137.5 dBc/Hz at 1 MHz offset from 2.53 GHz, demonstrating excellent phase noise suppression by the DHT tank. A very good figure-of-merit of −197.5 dBc/Hz is achieved.
Adaptive Neural Tracking for a Class of SISO Uncertain and Stochastic Nonlinear Systems

Adaptive neural control schemes based on the backstepping technique are developed to solve the tracking control problem of a combined stochastic and uncertain nonlinear system. As shown by an extensive stability analysis the proposed control scheme ensures that all the error variables are bounded in probability while the mean square tracking error becomes semiglobally uniformly ultimately bounded in an arbitrarily small area around the origin. The effectiveness of the design approach is illustrated by simulation results.
Substrats neuronaux du traitement visuel et sémantique des mots dans le vieillissement normal : apports de la MEG

words were examined specifically. Finally, the pattern of cortical activation associated with semantic processing in the group of healthy older adults was found to be overall more widespread than in the younger group, recruiting for instance posterior regions of the right-hemisphere to a greater extent. 4. Discussion The main goal of this study was to investigate the neural bases of semantic processing in healthy aging. In terms of cognitive performance, younger and older adults performed
Identification of Two Spliced Leader RNA Transcripts from Perkinsus marinus

ABSTRACT. Spliced leader (SL) variants are present in a number of mRNAs from Perkinsus marinus. Three different SLs of 22 nucleotides (nt) in length were previously reported, with a consensus sequence of (DCCGUAGCCAUYUUGGCUCAAG). A truncated 21 nt SL, with an (A) at nt‐1 and a (U) deletion at nt‐13, has also been reported. Here, we report an additional 21 nt SL variant with (G) at nt‐1. Using cDNA analysis, a full‐length SL RNA transcript was identified for both 21 nt SLs (SL2[A] and SL2[G]). This transcript is 81 nt in length and contains a conserved transcription termination sequence present in closely related dinoflagellates.
Drama groups Stigma challenging and well-being of individuals with HIV / AIDS in Uganda Dramagrupper

The purpose of this narrative study was to describe the role and potentials of drama groups for enhancing and maintaining well-being for female drama group members living with HIV in Uganda. Six semi-structured interviews were carried out and analyzed through a thematic analysis. The analysis was made within a theoretical framework based upon Sen's notion of the capability approach and social psychological theories of the self. The results showed that the activities carried out by the drama group empowered the women through increasing their access to important capabilities such as inclusion and self-respect. It further indicated that the women needed other forms of support before being able to benefit from these activities. However, some capabilities were still inaccessible to the women due to obstacles as poverty and harmful gender norms.
Patterns of Affective Reactions to Advertisements: The Integration of Moment-to-Moment Responses into Overall Judgments

The authors develop several hypotheses regarding the integration of moment-to-moment emotional responses into overall ad judgments, using the psychological literature dealing with people's preferences for sequences of hedonic outcomes, and they conduct three studies to test these predictions. The results of Study 1 indicate that consumers’ global assessments of extended affective episodes elicited by advertisements are dominated by the peak emotional experience and the final moment of the series and also are correlated with the pace at which momentary affective reactions improve over time. Ad duration is related only weakly to overall ad judgments, though longer advertisements have an advantage as long as they build toward a peak emotional experience. In Study 2, the authors replicate these findings under more realistic viewing conditions and demonstrate that the results cannot be attributed solely to memory artifacts that are based on recency. Study 3 implicates adaptation as a possible explanation for the preference for delayed peaks and high ends and further explains the weak effects of ad duration by showing experimentally that longer advertisements can both enhance and depress ad judgments depending on how duration affects the peak emotional experience and the final moment.
Pashto speech recognition with limited pronunciation lexicon

Automatic speech recognition (ASR) for low resource languages continues to be a difficult problem. In particular, colloquial dialects of Arabic, Farsi, and Pashto pose significant challenges in pronunciation dictionary creation. Therefore, most state-of-the-art ASR engines rely on the grapheme-as-phoneme approach for creating pronunciation dictionaries in these languages. While the grapheme approach simplifies ASR training, it performs significantly worse than a system trained with a high-quality phonetic dictionary. In this paper, we explore two techniques for bridging the performance gap between the grapheme and the phonetic approaches, without requiring manual pronunciations for all the words in the training data. The first approach is based on learning letter-to-sound rules from a small set of manual pronunciations in Pashto, and the second approach uses a hybrid phoneme/grapheme representation for recognition. Through experimental results on colloquial Pashto, we demonstrate that both techniques perform as well as a full phonetic system while requiring manual pronunciations for only a small fraction of the words in the acoustic training data.
A Hybrid Set-up Optimization Model for Tandem Cold Rolling Mill

: Set-up optimization of the rolling process involves several parameters that may lead to complex multi objective optimization problem. Also, it is well known that experience is playing a vital role in the selection of operating parameters in rolling mill. This paper presents a combination of two optimization procedure for a multi objective optimization problem. The first optimization phase is based on Nelder and Mead simplex method which focus on balance of power, force and reduction distribution in set-up planning. Then, a real-coded genetic algorithm based optimization procedure applies on the system as an outer loop to optimize energy consumption and productivity. An experimental result of application to five stand tandem cold rolling mill is presented.
ON THE USE OF GEOMETRIC AND SEMANTIC MODELS FOR COMPONENT-BASED BUILDING RECONSTRUCTION

3D building data is needed in many application areas. Besides the geometric description an increasing number of applications also demand thematic information about acquired buildings. We present a concept for the automatic extraction of buildings from aerial images. In contrast to other approaches generic building structures both are geometrically reconstructed and semantically classified. A component-based, parameterized building model is employed to control the reconstruction of buildings. This paper describes how geometric and semantic knowledge of buildings is propagated through the different aggregation levels of the building model. Furthermore, it is shown how rules and constraints are derived from the model and exploited at each stage of the reconstruction process.
Synchronization of Time-delayed Systems Via Learning Control

In this paper, a learning control approach is applied to the synchronization of two uncertain chaotic systems which contain nonlinear uncertainties with unknown time delays. This learning approach also deals with unknown time-varying parameters having distinct periods in the master and slave systems. Using the Lyapunov-Krasovskii functional and incorporating periodic parametric learning mechanism, global stability and asymptotic synchronization between the master and the slave systems are obtained. Simulation studies on representative classes of chaotic systems demonstrate the effectiveness of the proposed approach
Identifying optimal biomarker combinations for treatment selection through randomized controlled trials

Background/Aims Biomarkers associated with treatment-effect heterogeneity can be used to make treatment recommendations that optimize individual clinical outcomes. To accomplish this, statistical methods are needed to generate marker-based treatment-selection rules that can most effectively reduce the population burden due to disease and treatment. Compared to the standard approach of risk modeling to derive treatment-selection rules, a more robust approach is to directly minimize an unbiased estimate of total disease and treatment burden among a pre-specified class of rules. This problem is one of minimizing a weighted sum of 0–1 loss function, which is computationally challenging to solve due to the nonsmoothness of 0–1 loss. Huang and Fong, among others, proposed a method that uses the Ramp loss to approximate the 0–1 loss and solves the minimization problem through repetitive constrained optimizations. The algorithm was shown to have comparable or better performance than other comparative estimators in various settings. Our aim in this article is to further extend the algorithm to allow for variable selection in the presence of a large number of candidate markers. Methods We develop an alternative method to derive marker combinations to minimize the weighted sum of Ramp loss in Huang and Fong, based on data from randomized trials. The new algorithm estimates treatment-selection rules by repetitively minimizing a smooth and differentiable objective function. Through the use of an L1 penalty, we expand the method to allow for feature selection and develop an algorithm based on the coordinate descent method to build the treatment-selection rule. Results Through extensive simulation studies, we compared performance of the proposed estimator to four existing approaches: (1) a logistic regression risk modeling approach, and three other “direct optimizing” approaches including (2) the estimator in Huang and Fong, (3) the weighted support vector machine, and (4) the weighted logistic regression. The proposed estimator performs comparably to that of Huang and Fong, and comparably or better than other estimators. Allowing for variable selection using the proposed estimator in the presence of a large number of markers further improves treatment-selection performance. The proposed estimator is also advantageous for selecting variables relevant to treatment selection compared to L1 penalized logistic regression and weighted logistic regression. We illustrate the application of the proposed methods in host-genetics data from an HIV vaccine trial. Conclusion The proposed estimator is appealing considering its effectiveness and conceptual simplicity. It has significant potential to contribute to the selection and combination of biomarkers for treatment selection in clinical practice.
Developmental, emotional and behavioral co-morbidities across the chronic health condition spectrum.

AIMS Estimate the prevalence of specific developmental, emotional, and behavioral (DEB) problems across selected chronic health conditions; examine the relationship of chronic health conditions to functional activities and participation; determine the potential confounding effect of sociodemographic factors on the prevalence of DEB problems. METHODS The 2007 National Survey of Children's Health, conducted by the Centers for Disease Control and Prevention, served as the primary data source for this study. A total of 91.642 interviews (66.6% response rate for identified households with children) were performed. Population-based estimates were obtained for variables of interest by assigning sampling weights to each child for whom an interview was completed. RESULTS Parents were two to 30 times more likely to report DEB problems, such as Attention Deficit/Hyperactivity Disorder, depression, learning problems, and challenging behaviors, for children with chronic health conditions. These children had a greater number and range of difficulties with social interaction and school functioning as well as a lower rate of participation in community activities. Although highest rates of DEB problems were reported for those conditions involving the nervous or sensory systems, children with asthma, diabetes, and musculoskeletal conditions also had a higher rate of problems than children without the conditions. The higher prevalence of DEB problems remained after statistical adjustment for socio-demographic factors. CONCLUSIONS Children with a spectrum of chronic health conditions are at high risk for DEB problems that affect learning, behavior, and emotional well-being. As part of a comprehensive approach to the management of chronic health conditions, children should be screened for these problems and referred for appropriate further evaluation and remediation. Attention to these common co-morbidities will not only result in enhanced quality of life but will also promote better adherence to medical recommendations and, thereby, optimal disease control.
Brain-CAVE Interface Based on Steady-State Visual Evoked Potential

Recently, a new modality of the human-computer interface has been more and more emerging; The Brain-Computer Interface (BCI). The BCI is a communication channel, which enables us to send commands to external devices by using human brain activities (Wolpaw et al., 2002). As one of the remarkable achievements, we can see the report on invasive Brain-Machine Interface (BMI) (Hochberg et al., 2006). Besides the technique of the invasive BMI, there are several types of non-invasive approaches for the brain signal acquisitions; for example, functional magnetic resonance imaging (fMRI), near infrared spectroscopy (NIRS), etc. Non-invasive methods have been noteworthy owing to the recent development of the signal processing method as well as acquisition apparatus. The performance of the BCI system is going to be improved and the applications has been seen; for example, the communication tool for people with disability, virtual reality games, and so on. Among them, the electroencephalography (EEG) has been investigated as one of the candidates for the low-cost and portable BCI system. It is well known that the EEG activities can be detected by the scalp recording, which are typically the order of 5-10 micro volts of potentials. The BCI system can extract the specific temporal and spatial patterns from the brain potentials, and translates them into the commands to control the machine according to the users’ intent. A variety of brain activities has been reported so far in the context of the BCI systems based on EEG signals; for instance, motor related potential (Pfurtscheller & Neuper, 1997), event related P300 evoked potential (Farwell & Donchin, 1988), visual evoked potential (VEP) (Kuroiwa & Celesia, 1981), etc. With such brain activities, many applications have been developed in laboratories such as a virtual keyboard or joystick. However, most of them were studied on the system with the simple visual feedback involving a normal computer monitor. The purpose of this book chapter is to show the technique to realize a BCI system in virtual reality environment and to suggest the possibility of the online control of computergenerated objects. Note that the most advantage of testing the BCI system in virtual reality is that we can easily test and simulate procedures for the BCI applications in reality (Pfurtscheller et al., 2006). Our works are based on the VEP, which is expected to yield high performance BCI systems. In spite of the expected use of the VEP, the BCI system based on such EEG oscillations has never reported in immersive virtual environments.