Miracle-dz/UniFAR-FTUs huggingface dataset:
How do high performance work systems influence organizational innovation in professional service firms

Purpose – The purpose of this paper is to examine how a system of human resource management (HRM) practices, labelled high-performance work systems (HPWS), influences organizational innovation in professional service firms (PSFs). In this study, innovation in PSFs is seen as an indicator of firm performance and is calculated as the revenue per person generated from new clients and new services, respectively. Design/methodology/approach – Quantitative data were collected from 195 managing partners, HR managers or experienced Partners in 120 Irish accounting firms. Hierarchical regression analysis was used to test the hypotheses. Findings – The analysis results indicate strong support for the mediating role of employees’ innovative work behaviours in the relationship between HPWS and two types of PSFs’ innovation performance. Practical implications – Managers need to effectively adopt and implement innovation-based HRM practices to encourage and support employees’ creative thinking and innovation. Through the adoption and utilization of these practices managers can enhance the firm’s innovation and its performance. Originality/value – This study contributes to our understanding of the link between HRM and firm innovation by explicating a pathway between these variables. This study also generalizes consistent findings on the HRM-firm innovation relationship to a different context, i.e. PSFs.
Development of a biofilm inhibitor molecule against multidrug resistant Staphylococcus aureus associated with gestational urinary tract infections

Urinary Tract Infection (UTI) is a globally widespread human infection caused by an infestation of uropathogens. Eventhough, Escherichia coli is often quoted as being the chief among them, Staphylococcus aureus involvement in UTI especially in gestational UTI is often understated. Staphylococcal accessory regulator A (SarA) is a quorum regulator of S. aureus that controls the expression of various virulence and biofilm phenotypes. Since SarA had been a focussed target for antibiofilm agent development, the study aims to develop a potential drug molecule targeting the SarA of S. aureus to combat biofilm associated infections in which it is involved. In our previous studies, we have reported the antibiofilm activity of SarA based biofilm inhibitor, (SarABI) with a 50% minimum biofilm inhibitory concentration (MBIC50) value of 200 μg/mL against S. aureus associated with vascular graft infections and also the antibiofilm activity of the root ethanolic extracts of Melia dubia against uropathogenic E. coli. In the present study, in silico design of a hybrid molecule composed of a molecule screened from M. dubia root ethanolic extracts and a modified SarA based inhibitor (SarABIM) was undertaken. SarABIM is a modified form of SarABI where the fluorine groups are absent in SarABIM. Chemical synthesis of the hybrid molecule, 4-(Benzylamino)cyclohexyl 2-hydroxycinnamate (henceforth referred to as UTI Quorum-Quencher, UTIQQ) was then performed, followed by in vitro and in vivo validation. The MBIC50 and MBIC90 of UTIQQ were found to be 15 and 65 μg/mL, respectively. Confocal laser scanning microscopy (CLSM) images witnessed biofilm reduction and bacterial killing in either UTIQQ or in combined use of antibiotic gentamicin and UTIQQ. Similar results were observed with in vivo studies of experimental UTI in rat model. So, we propose that the drug UTIQQ would be a promising candidate when used alone or, in combination with an antibiotic for staphylococcal associated UTI.
How Much Should We Trust the Dictator ’ s GDP Estimates ?

I study the manipulation of GDP statistics in weak and non-democracies. I show that the elasticity of official GDP figures to nighttime lights is systematically larger in more authoritarian regimes. This autocracy gradient in the night-lights elasticity of GDP cannot be explained by differences in a wide range of factors that may affect the mapping of night lights to GDP, such as economic structure, statistical capacity, rates of urbanization or electrification. The gradient is larger when there is a stronger incentive to exaggerate economic performance (years of low growth, before elections or after becoming ineligible for foreign aid) and is only present for GDP sub-components that rely on government information and have low third-party verification. The results indicate that yearly GDP growth rates are inflated by a factor of between 1.15 and 1.3 in the most authoritarian regimes. Correcting for manipulation substantially changes our understanding of comparative economic performance at the turn of the XXI century.
Benefits from U.S. Monetary Policy Experimentation in the Days of Samuelson and Solow and Lucas

A policy maker knows two models. One implies an exploitable inflation-unemployment trade-off, the other does not. The policy maker's prior probability over the two models is part of his state vector. Bayes' law converts the prior probability into a posterior probability and gives the policy maker an incentive to experiment. For models calibrated to U.S. data through the early 1960s, we compare the outcomes from two Bellman equations. The first tells the policy maker to "experiment and learn. " The second tells him to "learn but don't experiment. " In this way, we isolate a component of government policy that is due to experimentation and estimate the benefits from intentional experimentation. We interpret the Bellman equation that learns but does not intentionally experiment as an "anticipated utility" model and study how well its outcomes approximate those from the "experiment and learn" Bellman equation. The approximation is good. For our calibrations, the benefits from purposeful experimentation are small because random shocks are big enough to provide ample unintentional experimentation. Copyright 2007 The Ohio State University.
Epidemiological evidence of effects of coarse airborne particles on health

Studies on health effects of airborne particulate matter (PM) have traditionally focused on particles <10 μm in diameter (PM10) or particles <2.5 μm in diameter (PM2.5). The coarse fraction of PM10, particles >2.5 μm, has only been studied recently. These particles have different sources and composition compared with PM2.5. This paper is based on a systematic review of studies that have analysed fine and coarse PM jointly and examines the epidemiological evidence for effects of coarse particles on health. Time series studies relating ambient PM to mortality have in some places provided evidence of an independent effect of coarse PM on daily mortality, but in most urban areas, the evidence is stronger for fine particles. The few long-term studies of effects of coarse PM on survival do not provide any evidence of association. In studies of chronic obstructive pulmonary disease, asthma and respiratory admissions, coarse PM has a stronger or as strong short-term effect as fine PM, suggesting that coarse PM may lead to adverse responses in the lungs triggering processes leading to hospital admissions. There is also support for an association between coarse PM and cardiovascular admissions. It is concluded that special consideration should be given to studying and regulating coarse particles separately from fine particles.
You-Do, I-Learn: Unsupervised Multi-User egocentric Approach Towards Video-Based Guidance

This paper presents an unsupervised approach towards automatically extracting video-based guidance on object usage, from egocentric video and wearable gaze tracking, collected from multiple users while performing tasks. The approach i) discovers task relevant objects, ii) builds a model for each, iii) distinguishes different ways in which each discovered object has been used and iv) discovers the dependencies between object interactions. The work investigates using appearance, position, motion and attention, and presents results using each and a combination of relevant features. Moreover, an online scalable approach is presented and is compared to offline results. The paper proposes a method for selecting a suitable video guide to be displayed to a novice user indicating how to use an object, purely triggered by the user's gaze. The potential assistive mode can also recommend an object to be used next based on the learnt sequence of object interactions. The approach was tested on a variety of daily tasks such as initialising a printer, preparing a coffee and setting up a gym machine.
Head Pose Estimation using Deep Learning

Head poses are an important mean of non-verbal human communication and thus a crucial element in human-computer interaction. While computational systems have been trained with various methods for head pose estimation in the recent years, approaches based on convolutional neural networks (CNNs) for image processing have so far proven to be one of the most promising ones. This master’s thesis starts of improving head pose estimation by reimplementing a recent CNN approach based on the shallow LeNet-5. As a new approach in head pose estimation, this thesis focuses on residual networks (ResNets), a subgroup of CNNs specifically optimized for very deep networks. To train and test the approaches, the Annotated Facial Landmarks in the Wild (AFLW) dataset and the Annotated Faces in the Wild (AFW) benchmark dataset were used. The performance of the reimplemented network and the implemented ResNets of various architectures were evaluated on the AFLW dataset. The performance is hereby measured in mean absolute error and accuracy. Furthermore, the ResNets with a depth of 18 layers were tested on the AFW dataset. The best performance of all implemented ResNets was achieved by the 18 layer ResNet adapted for an input size of 112 x 112 pixels. In comparison with the reimplemented network and other state-of-the-art approaches, the best ResNet performs equal or better on the AFLW dataset and outperforms on the AFW dataset.
UvA-DARE ( Digital Academic Repository ) Implementing glucose control in intensive care : a multicenter trial using statistical process control

Background: Glucose control (GC) with insulin decreases morbidity and mortality of critically ill patients. In this study we investigated GC performance over time during implementation of GC strategies within three intensive care units (ICUs) and in routine clinical practice. Methods: All adult critically ill patients who stayed for [24 h between 1999 and 2007 were included. Effects of implementing local GC guidelines and guideline revisions on effectiveness/efficiency-related indicators, safety-related indicators, and protocol-related indicators were measured. Results: Data of 17,111 patient admissions were evaluated, with 714,141 available blood glucose levels (BGL) measurements. Mean BGL, time to reach target, hyperglycemia index, sampling frequency, percentage of hyperglycemia events, and in-range measurements statistically changed after introducing GC in all ICUs. The introduction of simple rules on GC had the largest effect. Subsequent changes in the protocol had a smaller effect than the introduction of the protocol itself. As soon as the protocol was introduced, in all ICUs the percentage of hypoglycemia events increased. Various revisions were implemented to reduce hypoglycemia events, but levels never returned to those from pre-implementation. More intensive implementation strategies including the use of a decision support system resulted in better control of the process. Conclusion: There are various strategies to achieve GC in routine clinical practice but with variable success. All of them were associated with an increase in hypoglycemia events, but GC was never stopped. Instead, these events have been accepted and managed. Statistical process control is a useful tool for monitoring phenomena over time and captures within-institution changes.
Variations of PM10 Pollution Index in Shanghai during Recent 9 Years

By wavelet analysis of daily PM10 pollution index in recent 9 years in Shanghai, the multi-scale variations, primary period and influencing factors are analyzed. The result shows the air pollution pattern presents “serious in winter and slight in summer” at most scales; varies at diverse time-scales, and the primary period of the daily variations is about quasi seasonal.
Estimate of fundamental period of reinforced concrete buildings : code provisions vs . experimental measures in Victoria and Vancouver ( BC , Canada )

The fundamental period of a group of reinforced concrete (RC) buildings located in the cities of Victoria and Vancouver (British Columbia, Canada) has been estimated using ambient vibration data. As result a preliminary heightdependent relationship has been derived for a fully elastic condition. The regression returns very similar values respect to those obtained in other countries using the system identification technique based on ambient vibrations. As expected, the results show that building periods estimated based on simple equations provided by earthquake design codes in Europe (EC8) and North America (UBC97 and NBCC-2005) are significantly greater than the periods computed using ambient vibration records on the monitored buildings.
Structural breaks in panel data: Large number of panels and short length time series

ABSTRACT The detection of (structural) breaks or the so called change point problem has drawn increasing attention from the theoretical, applied economic and financial fields. Much of the existing research concentrates on the detection of change points and asymptotic properties of their estimators in panels when N, the number of panels, as well as T, the number of observations in each panel are large. In this paper we pursue a different approach, i.e., we consider the asymptotic properties when N→∞ while keeping T fixed. This situation is typically related to large (firm-level) data containing financial information about an immense number of firms/stocks across a limited number of years/quarters/months. We propose a general approach for testing for break(s) in this setup. In particular, we obtain the asymptotic behavior of test statistics. We also propose a wild bootstrap procedure that could be used to generate the critical values of the test statistics. The theoretical approach is supplemented by numerous simulations and by an empirical illustration. We demonstrate that the testing procedure works well in the framework of the four factors CAPM model. In particular, we estimate the breaks in the monthly returns of US mutual funds during the period January 2006 to February 2010 which covers the subprime crises.
Inhibition of E. coli and S. aureus with selenium nanoparticles synthesized by pulsed laser ablation in deionized water

Nosocomial diseases are mainly caused by two common pathogens, Escherichia coli and Staphylococcus aureus, which are becoming more and more resistant to conventional antibiotics. Therefore, it is becoming increasingly necessary to find other alternative treatments than commonly utilized drugs. A promising strategy is to use nanomaterials such as selenium nanoparticles. However, the ability to produce nanoparticles free of any contamination is very challenging, especially for nano-medical applications. This paper reports the successful synthesis of pure selenium nanoparticles by laser ablation in water and determines the minimal concentration required for ~50% inhibition of either E. coli or S. aureus after 24 hours to be at least ~50 ppm. Total inhibition of E. coli and S. aureus is expected to occur at 107±12 and 79±4 ppm, respectively. In this manner, this study reports for the first time an easy synthesis process for creating pure selenium to inhibit bacterial growth.
Towards Automatically Penalizing Multimedia Breaches

This work studies the problem of automatically penalizing intentional or unintentional data breach (APB) by a receiver/custodian receiving confidential data from a sender. We solve this problem for multimedia data by augmenting a blockchain on-chain smart contract between the sender and receiver with an off-chain cryptographic protocol, such that any significant data breach from the receiver is penalized through a monetary loss. Towards achieving the goal, we develop a natural extension of oblivious transfer called doubly oblivious transfer (DOT) which, when combined with robust watermarking and a claim-or-refund blockchain contract provides the necessary framework to realize the APB protocol in a provably secure manner. In our APB protocol, a public data breach by the receiver leads to her Bitcoin (or other blockchain) private signing key getting revealed to the sender, which allows him to penalize the receiver by claiming the deposit from the claimor-refund contract. Interestingly, the protocol also ensures that the malicious sender cannot steal the deposit, even as he knows the original multimedia document or releases it in any form. We implement our APB protocol, develop the required smart contract for Bitcoin and observe our system to be efficient and easy to deploy in practice for multimedia documents. We analyze our DOT-based design against partial adversarial leakages and observe it to be robust against even small leakages.
Cognitive advantages of immersion education after 1 year

Previous studies with bilingual children have shown that the nature of their L2 instruction has an effect on the development of their cognitive abilities. The aim of this study was to determine whether children who acquire a second language in two different immersion programs for a period of one year show advantages in executive functions and to examine how the amount of daily exposure affects executive functions. A group of Serbian-speaking second grade children exposed to the second language for five hours a day (high exposure group, HEG), and a low exposure group (LEG) exposed to the second language for one and a half hours a day were compared to an age-matched control group (CG) of monolingual peers on working memory, inhibition and shifting. Significant group differences were found for working memory, with the HEG performing better than the CG and the LEG, even after controlling for individual differences in terms of age and intelligence. The three groups did not differ in terms of inhibition and overall shifting abilities, although the control group had a marginally significant advantage on one of the two shifting tasks. Our findings extend previous research by demonstrating that the amount of daily exposure is a significant factor affecting executive functions in early immersion programs for second language acquisition. Additionally, they show that early intensive second language acquisition can be advantageous for performance on tasks that require a higher level of executive control.
Interbank Liquidity Crunch and the Firm Credit Crunch: Evidence from the 2007-2009 Crisis

We study the credit supply effects of the unexpected freeze of the European interbank market, using exhaustive Portuguese loan-level data. We find that banks that rely more on interbank borrowing before the crisis decrease their credit supply more during the crisis. The credit supply reduction is stronger for firms that are smaller, with weaker banking relationships. Small firms cannot compensate the credit crunch with other sources of debt. Furthermore, the impact of illiquidity on the credit crunch is stronger for less solvent banks. Finally, we find no overall positive effects of central bank liquidity but instead higher hoarding of liquidity. The Author 2013. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com. , Oxford University Press.
Photon gating in four-dimensional ultrafast electron microscopy

Significance In this contribution, we demonstrate a unique concept in the use of photon-induced near-field electron microscopy—combining one electron pulse and two optical pulses—as a probe for ultrafast dynamics of matter in electron microscopy. Photon–electron coupling permits the use of a short optical pulse to gate the electron pulse, which is serving as a probe of the ultrafast dynamics triggered by another optical pulse. This technique provides the high spatial and temporal resolution of the electron pulse and optical laser pulses, respectively, both in ultrafast electron microscopy (UEM) measurements. This development paves the way for numerous studies in imaging of matter not only with few femtosecond resolution but also with the potential for attosecond imaging in UEM. Ultrafast electron microscopy (UEM) is a pivotal tool for imaging of nanoscale structural dynamics with subparticle resolution on the time scale of atomic motion. Photon-induced near-field electron microscopy (PINEM), a key UEM technique, involves the detection of electrons that have gained energy from a femtosecond optical pulse via photon–electron coupling on nanostructures. PINEM has been applied in various fields of study, from materials science to biological imaging, exploiting the unique spatial, energy, and temporal characteristics of the PINEM electrons gained by interaction with a “single” light pulse. The further potential of photon-gated PINEM electrons in probing ultrafast dynamics of matter and the optical gating of electrons by invoking a “second” optical pulse has previously been proposed and examined theoretically in our group. Here, we experimentally demonstrate this photon-gating technique, and, through diffraction, visualize the phase transition dynamics in vanadium dioxide nanoparticles. With optical gating of PINEM electrons, imaging temporal resolution was improved by a factor of 3 or better, being limited only by the optical pulse widths. This work enables the combination of the high spatial resolution of electron microscopy and the ultrafast temporal response of the optical pulses, which provides a promising approach to attain the resolution of few femtoseconds and attoseconds in UEM.
Mobile robot localization technique using Web-based aerial photos

This paper describes a localization technique that permits mobile robots to accurately determine their positions and even to respond to unforeseen obstacles such as pedestrians. The effectiveness of the method is confirmed in trials using a model robot. Generally, robots are taught the layout of operational environment in order to localize self-position. This is normally done through the generation of an environmental map that is created by running the robot through every accessible area of the environment beforehand. This also means that such robots are unable to localize their positions in unknown environments. In this research, we propose a method that allows robots to perform self-position localization in unknown environments through the use of low-resolution photographs available through online services such as Google Maps. This research involves the application of a space observation model to a framework of self-position presumptions that do not rely on the extraction of strict edge information from aerial photographs. The validity of the proposed technique was verified through a presumptive self-position experiment conducted in an unknown environment using a map created from an aerial photograph.