Miracle-dz/UniFAR-FTUs huggingface dataset:
Hd28 .m414 No. Working Paper Alfred P. Sloan School of Management Windows of Opportunity: Creating Occasions for Technological Adaptation in Organizations Windows of Opportunity: Creating Occasions for Technological Adaptation in Organizations Windows of Opportunity: Creating Occasions for Technolog

This paper examines the introduction and ongoing adaptation of technologies that support productive operations. The authors suggest that ongoing improvement of new process technologies by user organizations is limited by increasing routinization that occurs with experience. Evidence from three manufacturing and service organizations indicates that there exists a relatively brief window of opp>ortunity to explore and change new process technology following initial implementation. Afterwards the technology and its context of use tend to congeal, often embedding unresolved problems into organizational practice. Further adaptation is difficult unless discrepant events provide new windows for revisiting previous choices and assumptions. Implications for conceptualizing and managing technological change in production environments are discussed. "Here is Edward Bear, coming downstairs now, bump, bump, bump, on the back of his head behind Christopher Robin. It is, as far as he knows, the only way of coming downstairs, but sometimes he feels that there really is another way, if only he could stop bumping for a moment and think of it. "
Protein Kinase Inhibitory Potential and Anti-Fungal Activities of Metal Complexes of Anti-Viral Drug Ribavirin

Background: Ribavirin, a known antiviral drug, potentially recognised for a number of pathological conditions like hepatitis C, Lassa fever and Hanta virus infection. It predominantly works by inhibiting viral RNA synthesis that in turn stop viral multiplication. The best prosperous derivative of this drug is Taribavirin (3-carboxamidine derivative). Objective: In this research, we aim to synthesize the metal complexes of already marketed drug ribavirin, because the complexation of such approved marketed drug will save time and currency that may spend in relation to clinical development of new drug molecule. Method: Eleven derivatives (S-01-S-11) of ribavirin were synthesized in combination with di/tri organotin, Zn, Cu and Fe. Characterization was done through IR and H1 NMR spectrophotometer and these compounds were analysed for in vitro biological activities including anti-microbial, anti-fungal and protein kinase inhibition assay. Results: Research revealed that addition of trace metals to approved marketed drug have enhanced the biological properties of unbound drug. Conclusion: Outcomes of this research clearly indicates the enhancement of biological activities of free drug through immersion of metals which could be further analysed for toxicity studies.
The Legal Framework for Academic Professional Development for Radiographers in Higher Education

Technology has changed the world of radiography, setting the request for development and promotion of radiography occupation. This article focuses on key factors of education for radiologic technologist / radiographer. The important role of EFRS in promoting and developing advanced educational standards and qualifications for radiographers is elaborated. Harmonization and development of radiographer’s profession following technological development considers cooperation among educational institutions, employers and professional bodies, within the framework of European and national legislation. Society should provide the conditions for further education. Obtaining a master's and / or doctoral degree, and integration in teaching and research activities, helps transform radiographers into leadership roles within their departments.
Investigating Energy Prosumer Behaviour in Crowd Energy Using an Interactive Model/Diorama

Smart living labs such as the one located in Fribourg (Switzerland) focus on improving wellbeing and furthering knowledge related to building the district of the future on a technical and social level. Therefore, smart living labs represent an experimental platform/space where sustainable production and consumption strategies can be tested in a protected environment. A significant change in the socioeconomic production and consumption sphere can be expected by the rise of the so-called energy prosumer. Accordingly, this article presents an interactive model for the experimental investigation of energy prosumer behavior. In this context, two potential experiments on investment and trade decisions are briefly outlined. Since (behavioral and economic) experiments are usually conducted under controlled conditions in experimental labs involving mainly undergraduate students, the presented interactive model is flexible and mobile, providing the advantage to conduct experiments nearly everywhere involving everyday citizens.
Scattering threshold for the focusing nonlinear Klein–Gordon equation

We show scattering versus blow-up dichotomy below the ground state energy for the focusing nonlinear Klein-Gordon equation, in the spirit of KenigMerle for the H critical wave and Schrödinger equations. Our result includes the H critical case, where the threshold is given by the ground state for the massless equation, and the 2D square-exponential case, where the mass for the ground state may be modified, depending on the constant in the sharp Trudinger-Moser inequality. The main difficulty is the lack of scaling invariance in both the linear and the nonlinear terms.
Lost in reading: The predicament of postcolonial writing in Kamel Daoud’s The Meursault Investigation

ABSTRACT Kamel Daoud’s novel The Meursault Investigation (first published in Algeria in 2013 as Meursault, contre-enquête) has sparked controversy. In 2014 it won awards in France and was nominated for the Prix Goncourt, and won the 2015 Goncourt First Novel Prize. At the same time, some radical Islamists accused Daoud of apostasy and called for his execution; others described him as having “sold out” to France. This article seeks to problematize the concept of “self-imposed ḥisba” and to dispute accusations made concerning The Meursault Investigation. It proposes a postcolonial reading that contests the perception of Daoud as a self-hating Arab complicit with the French, and draws on Homi Bhabha’s concepts of ambivalence and mimicry to trace the emergence of cultural forms that take debates about colonial/postcolonial representation to a new level. It argues that any reading of Daoud’s novel that fails to pay attention to the complex workings of its language is incomplete.
Intelligent Mining Association Rules

Association rules is one of data mining methods for discovering knowledge from large amounts of data in databases. In this paper, we propose an intelligent method for discovering association rules, called IMAR. IMAR is designed through three main phases, i.e., preprocessing, processing and post processing. It has been experimented using three domain data sets, i.e., Australian Credit Card (ACC), Jakarta Stock Exchange (JSX), and Cleveland Heart Diseases (CLEV) data sets. Our experimental results show that IMAR can (i) discover association rules from large inconsistent databases intelligently and accurately, and (ii) reduce the number of generated interesting association rules without losing information and with higher accuracy.
Multisensory stress reduction: a neuro-architecture study of paediatric waiting rooms

ABSTRACT The implementation of environmental satisfaction sources in the design of a health centre is a means to achieve stress reduction. The present work analyses the effect that these sources have on the stress reduction of patients’ companions in a paediatric service. A two-phase study was carried out. During the first phase, 120 participants assessed 20 waiting rooms in situ in order to select the environmental sources with the greatest effect. During the second phase, the stress levels of 26 participants were measured in four simulated waiting rooms that combined the selected sources from the first phase. A multisensory simulation was carried out through a virtual reality experiment with visual, auditory and olfactory elements, and stress levels were measured at the psychological and neurophysiological levels. Results suggest that a combination of environmental satisfaction sources creates an important synergistic effect at the psychological and neurophysiological levels and underlines the importance of auditory and olfactory stimuli. Conclusions may be of interest to designers and managers of healthcare facilities.
Evaluating Noise Sources in a Working
Environment when Disintegrating Rocks
by Rotary Drilling

The mechanical disintegration of rocks plays an irreplaceable role in the exploration, preparation, and mining of minerals resources in geological and engineering surveys. When disintegrating by rotary drilling, the disintegration tool interacts with the rock and converts the mechanical energy to thermal energy caused by the friction of the disintegration tool on the rock. Consequently, undesirable accompanying sounds occur in the process of disintegration of the rock by drilling. These include vibrations that show up in the working environment as noise. The noise generated during rotary drilling can be scanned as an acoustic signal. From above, it is possible to say that noise and vibration have a direct negative impact on the machinery personnel, on the working environment and on the environment. At present, research in the field of the disintegration of rocks by rotary drilling is directed at analyzing the factors affecting the disintegration of rocks and the working environment. This article analyzes experimental measurements carried out on a horizontal drilling tool. Measured vibroacoustic signals in different operating modes will be processed in the time, frequency, and time-frequency domains.
Research and Application of a Novel Combined Model Based on Multiobjective Optimization for Multistep-Ahead Electric Load Forecasting

Accurate forecasting of electric loads has a great impact on actual power generation, power distribution, and tariff pricing. Therefore, in recent years, scholars all over the world have been proposing more forecasting models aimed at improving forecasting performance; however, many of them are conventional forecasting models which do not take the limitations of individual predicting models or data preprocessing into account, leading to poor forecasting accuracy. In this study, to overcome these drawbacks, a novel model combining a data preprocessing technique, forecasting algorithms and an advanced optimization algorithm is developed. Thirty-minute electrical load data from power stations in New South Wales and Queensland, Australia, are used as the testing data to estimate our proposed model’s effectiveness. From experimental results, our proposed combined model shows absolute superiority in both forecasting accuracy and forecasting stability compared with other conventional forecasting models.
Finding common support through largest connected components and its implementation

In an observational study, the average treatment effect may only be reliably estimated for a subset of units under which the covariate space of both treatment and control units overlap. This is known as the common support assumption. In this report, we develop a method to find a region of common support. The method is as follows. Given a distance function to measure dissimilarity between any two units with differing treatment statuses, we can construct an adjacency list by drawing edges between each pair of treated and control units that have distance no larger than some pre-specified threshold. Then, all connected components of the graph are found. Finally, a region of common support is found by obtaining the largest connected components (LCC) (e.g. the connected components with the most treated units) of this graph. We implement the LCC algorithm by using binary search trees to find all the connected graphs from sample data and sorting them by size. This algorithm requires O(n) runtime and O(n) memory (where n is the number of units in the observational study. We then create an R package implementing this LCC algorithm. Finally, we use our R package to compare the performance of LCC to that of other common support methods on simulated data.
Steroid Influences on Respiration, Glycolysis, and Levels of in the present experiments multiple mammary cancers were induced in rats, and the levels of six soluble pyridine nucleotide-linked enzymes

in the present experiments multiple mammary cancers were induced in rats, and the levels of six soluble pyridine nucleotide-linked enzymes were determined in the tumors before and after (a) the withdrawal of steroids by oophorectomy, (b) the administration of sex steroids, (c) preg nancy, and (d) lactation. It was found that these modifications of the steroid status exerted great effects on the levels of lactic dehydrogenase,' glucose-6-phosphate dehydrogenase, and malic en zyme (TPN) in the cancers. Changes in the en docrine status exerted smaller effects on the levels in the tumors of 6-phosphogluconic dehydrogen ase, isocitric dehydrogenase and malic dehydro
'Examining international students’ expectations of third-party community engagement as a value co-creation mechanism

Purpose of the Study: In higher education, international university students may participate in third-party community engagement experiences (TPCE) as a value co-creation (VCC) mechanism (TPCEVCC), and the university may facilitate these experiences. Drawing from Payne et al.’s (2008) conceptual framework, this study examines how international students’ expected cognitions, emotions and behaviors contribute to their expectations of multi-stakeholder VCC experiences. Examining the international student experience in the context of third-party community engagement, allows marketers to better understand the holistic nature of marketing the international student experience and addresses the need for empirically focused VCC research, particularly at the onset of services and in multi-stakeholder scenarios. Method/Design and Sample: Two models were developed—a full and partially mediated model. Data from n=310 international students were collected via a survey administered at the onset of the international student experience. Data were subject to structural equation modelling. Results: Analysis revealed the strong influence of expected behaviors on expected TPCEVCC. International students expect to behaviorally participate in TPCEVCC and this may be partially facilitated by the university. Findings also suggest opportunities to connect earlier with students’ cognitions and emotions to optimize TPCEVCC, supporting better marketing strategies. Value to Marketing Educators: The study generates theoretical and practical insight for marketers, administrators and faculty to further enhance and develop the international student experience, along with other similar service experiences in higher education, benefiting student, university and community stakeholders.
Weeds in a Changing Climate

Current and projected increases in the concentrations of CO2 and other radiatively-active gases in the Earth's atmosphere lead to concern over possible impacts on agricultural pests. All pests would be affected by the global warming and consequent changes in precipitation, wind patterns, and frequencies of extreme weather events which may accompany the “greenhouse effect. ” However, only weeds are likely to respond directly to the increasing CO2 concentration. Higher CO2 will stimulate photosynthesis and growth in C3 weeds and reduce stomatal aperture and increase water use efficiency in both C3 and C4 weeds. Respiration, and photosynthate composition, concentration, and translocation may be affected. Perennial weeds may become more difficult to control, if increased photosynthesis stimulates greater production of rhizomes and other storage organs. Changes in leaf surface characteristics and excess starch accumulation in the leaves of C3 weeds may interfere with herbicidal control. Global warming and other climatic changes will affect the growth, phenology, and geographical distribution of weeds. Aggressive species of tropical and subtropical origins, currently restricted to the southern U.S., may expand northward. Any direct or indirect consequences of the CO2 increase that differentially affect the growth or fitness of weeds and crops will alter weed-crop competitive interactions, sometimes to the detriment of the crop and sometimes to its benefit.
Covert Channels-Based Stealth Attacks in Industry 4.0

Industry 4.0 advent opens several cyber-threats scenarios originally designed for classic information technology (IT), drawing the attention to serious risks for the modern industrial control networks. To cope with this problem, in this paper, we address the security issues related to covert channels applied to industrial networks, identifying the new vulnerability points when ITs converge with operational technologies such as edge computing infrastructures. Specifically, we define two signaling strategies where we exploit the Modbus/transmission control protocol (TCP) as target to set up a covert channel. Once the threat channel is established, passive and active offensive methodologies are further exploited by implementing and testing them on a real industrial Internet of Things testbed. The experimental results highlight the potential damage of such specific threats and the easy extrapolation of the attacks to other types of channels in order to show the new risks for the Industry 4.0. Related to this, we discuss some countermeasures offering an overview of possible mitigation and defensive measures.
Data cloning estimation for asymmetric stochastic volatility models

Abstract The paper proposes the use of data cloning (DC) to the estimation of general univariate asymmetric stochastic volatility (ASV) models with flexible distributions for the standardized returns. These models are able to capture the asymmetric volatility, the leptokurtosis and the skewness of the distribution of returns. Data cloning is a general technique to compute maximum likelihood estimators, along with their asymptotic variances, by means of a Markov chain Monte Carlo (MCMC) methodology. The main aim of this paper is to illustrate how easily general univariate ASV models can be estimated and consequently studied via data cloning. Changes of specifications, priors and sampling error distributions are done with minor modifications of the code. Using an intensive simulation study, the finite sample properties of the estimators of the parameters are evaluated and compared to those of a benchmark estimator that is also user-friendly. The results show that the proposed estimator is computationally efficient, and can be an effective alternative to the existing estimation methods applied to ASV models. Finally, we use data cloning to estimate the parameters of general ASV models and forecast the one-step-ahead volatility of S&P 500 and FTSE-100 daily returns.
OPTIMAL CHOICE OF MONETARY POLICY INSTRUMENTS IN A MACROECONOMETRIC MODEL*

Nearly twenty years ago today Poole (1970) wrote his classic article on the optimal choice of monetary policy instruments in a stochastic IS-LM model. Poole assumed that the monetary authority (henceforth called the Fed) can control the interest rate (r) or the money supply (M) exactly. These are the two ‘instruments’ of monetary policy. If the aim is to minimize the squared deviation of real output from its target value, Poole showed that the choice of the optimal instrument depends on the variance of the error term in the IS function, the variance of the error term in the LM function, the covariance of the two error terms, and the size of the parameters. Most people would probably agree that between about October 1979 and October 1982 the Fed put more emphasis on monetary aggregates than it did either before or after. Otherwise, the interest rate has seemed to be the Fed’s primary instrument. It is interesting to ask if the use of the interest rate can be justified on the basis of the Poole analysis. Is the economy one in which the variances, covariances, and parameters are such as to lead. a la the Poole analysis, to the optimal instrument being the interest rate?
Hardware Acceleration for Tensorized Neural Networks

Author(s): Gan, Yiming | Advisor(s): Xie, Yuan | Abstract: Machine learning has gained success in many application domains including medical data analysis, finance, computer vision, and so forth. However, many popular machine learning models (e.g., deep neural networks) are both data-intensive and computationally expensive: they require high-volume data samples to train the networks, millions to billions of parameters to describe the model, and large-scale computations to complete the optimization or inference. Therefore, deep learning can cause unaffordable energy and run-time cost on a hardware platform. In this paper, we present a way of accelerating deep neural networks as well as compressing weights used by designing hardware acceleration for tensor train decomposition layers in deep neural networks. By utilizing hardware acceleration on tensorized neural networks, we achieved massive memory saving on two fully -connected layers. Parameters shrink 4880644x and 3195660x respectively. At the same time, we achieve speed up at 2600x and 2900x compared to original matrix multiplication process.
A study of mobility models for UAV Communication Networks

The Unmanned aerial vehicle communication network (UAVCN) is a group or swarm of unmanned aerial vehicles which can be used for specific military and civilian applications without human intercession. This network faces the design problem which is based on network mobility. The frequent topology changes affect communication and collaboration among the UAVs (Unmanned aerial vehicles). To govern the movement pattern of UAVCN different mobility models needed to be studied in order to solve this communication issue. In this paper, mobility models are explored which provides the particular mobility pattern to resolve the problem of collaboration, communication and cooperation of UAVs. These models have been categorized into five groups and classified each group in detail. These mobility models provide the platform to understand and implement the unmanned aerial communication network for specific environment scenarios. The mobisim simulator tool is used to generate the mobility model s trajectories for different mobility models.
Surviving Employees’ Perception of Downsizing and it’s Impact on their Job Involvement and Job Security : The Ghanaian Experience

The study was basically to examine surviving employees’ perception of downsizing and how three critical conditions (i.e. closeness of survivor to victim, previous experience with downsizing and one’s status in the organizational hierarchy) affect them in relation to their work attitudes (Job Involvement and Job Security). In all, 200 employees participated in the study. Results of the study indicate that survivors’ relationship with affected victims influenced their job involvement such that, those whose relations/ friends were laid off showed lower job involvement than those whose victims were mere coworkers. Another finding was that, employees who had previously experienced or witnessed a downsizing exercise prior to the recent one showed greater job security than their counterparts who had never experienced any downsizing. Finally, senior level employees felt more involved in their jobs than their junior counterparts. In view of the findings, it is recommended that organizations should manage downsizing programmes in ways that would not disrupt social networks unnecessarily. In addition, management must ensure transparency to reduce the anxiety that characterizes these exercises.