Miracle-dz/UniFAR-FTUs huggingface dataset:
M2746 - ROSE-ACKERMAN 9781849802512 PRINT.indd

Corruption occurs where the private search for economic advantage and personal advancement clashes with laws and norms that condemn such behavior. Further complicating the picture, some illegal corrupt transactions accord with social norms favoring one’s family, friends, and ethnic group. Other actions may be formally legal but have harmful eff ects similar to outright bribery. Reformers often label practices ‘corrupt’ simply because they disapprove of them, but economists seek a more objective concept that they can study theoretically and empirically and then evaluate for its normative characteristics. As many of the chapters in this volume demonstrate, one must study corruption in context. Understanding the consequences of corrupt transactions requires one to know what is being bought with a bribe and how the behavior of public and private actors has been aff ected. What will happen if corruption is reduced? Will other forms of favoritism and selfdealing of marginal legality substitute for outright payoff s and kickbacks, or will the result be an honest and wellfunctioning system? Reformers must address the underlying institutional and social conditions that encourage this behavior. Is corruption the sideeff ect of a larger problem of monopolistic behavior or entrenched organized crime infl uence? If so, eliminating corruption may simply benefi t the bribe payers who may continue to operate with impunity. This volume complements Susan RoseAckerman’s fi rst International Handbook on the Economics of Corruption (2006). That volume began by introducing readers to debates over the value of crosscountry indices that aggregate perceptions of corruption to permit international comparisons. These indices appear to capture the extent of dysfunctional relations between state and society, including the international business community. However, they are very vague and poorly defi ned. They do a good job of diff erentiating states that are deeply dysfunctional from those countries where corruption exists in particular locations and sectors but is not systemic. However, for the wide range of countries in the middle range, the indices tell us nothing about the relative importance of bribery, extortion, and other forms of selfdealing in diff erent sectors. Yet, in fact, there appears to be wide variation in the types of corruption that are most prevalent in diff erent countries. To progress, more disaggregated research
Climate change impact of wind energy availability in the Eastern Mediterranean using the regional climate model PRECIS

Global near-surface wind fields are projected to change as a result of climate change. An enhanced knowl- edge of the changes in wind energy availability in the twenty- first century is essential for improving the development of wind energy production. We use the PRECIS regional model over the East Mediterranean to dynamically downscale the results of the Had3CM Atmosphere-Ocean coupled Global Circulation Model. Wind field changes during the 21st cen- tury are determined by comparing the current climate sim- ulation (1961-1990) with the IPCC A2 emissions scenario simulation (2071-2100). The consistency of the current cli- mate simulation of wind speeds is assessed by comparing its results to the ERA40 re-analysis data. The comparison of the wind field from ERA40 re-analysis to that from the PRE- CIS current climate simulation shows relatively large mean differences that could partly be attributed to the difference in the spatial resolution of the two sources of data. Wind speeds in 2071-2100 exhibit a general increase over land and a de- crease over the sea, with the exception of a noticeable in- crease over the Aegean Sea.
An Instrument for Assessing Upper-Division Engineering Students' Efficacy Beliefs about Mathematics

The factor validity of a pilot instrument to assess upper-division engineering students’ selfefficacy beliefs (SE beliefs) about their lower-division mathematics was established. The instrument aimed at identifying how junior and senior engineering students relate their lowerdivision mathematics knowledge to the solution of upper-division engineering problems in two disciplines: Electrical & Computer Engineering and Mechanical Engineering. The pilot instrument was used to predict a priori the hypothesis that those students who believe that solving core, upper-division engineering problems is: (a) influenced by their effective use of lower-division mathematics (i.e., their outcome expectancies or OE beliefs); (b) who also have confidence in their own mathematical abilities (SE beliefs) should be more skilled at setting-up and solving these problems. The instrument was subjected to a confirmatory factor analysis using the structural modeling feature in SAS, v.9. Reliability analysis produced a Cronbach’s  coefficient of 0.862 for the mathematics SE beliefs scale and a Cronbach’s  coefficient of 0.797 for the OE scale (n = 49). The current standard is that 0.7   < 0.8 is good and that 0.8   < 0.9 is very good. These results provide evidence that the pilot instrument items measure an underlying (latent) construct. Confirmatory factor analysis indicates that these two scales are independent, thus adding to the construct validity of this instrument. The paper concludes with a discussion concerning how students’ SE and OE beliefs are postulated to affect students’ problem solving skills of upper-division electrical and mechanical engineering problems.
Low-mass Star Formation: Observations

Abstract I briefly review recent observations of regions forming low mass stars. The discussion is cast in the form of seven questions that have been partially answered, or at least illuminated, by new data. These are the following: where do stars form in molecular clouds; what determines the IMF; how long do the steps of the process take; how efficient is star formation; do any theories explain the data; how are the star and disk built over time; and what chemical changes accompany star and planet formation. I close with a summary and list of open questions.
Metabolism of polycyclic aromatic hydrocarbons by the microbiome of the human skin

Content 1\. Introduction 1 1.1 The Skin – A Sensory and Protective Organ 1 1.2 The Human Microbiome – the human body as a host 2 1.2. 1 Composition of the skin microbiome 2 1.2. 2 Development of the individual microbial fingerprint 3 1.2. 3 The interrelationship between the host and the microbiome 5 1.2. 4 Xenobiotic metabolism of the human microbiome 6 1.3 Polycyclic Aromatic Hydrocarbons (PAHs) 7 1.3.1 Chemical properties of polycyclic aromatic hydrocarbons 7 1.3.2 Origin, occurrence and exposure of PAHs 9 1.4 Metabolism of B[a]P in human cells 10 1.5 Biological degradation of geoaccumulated polycyclic aromatic hydrocarbons in environmental microbiology 14 1.5. 1 Microbial isolates from soil microbiology and their potential to metabolise HMW PAHs 14 1.5. 2 Biotic and abiotic factors that influence microbial PAH degradation. 17 1.5. 3 The model organism Mycobacterium vanbaalenii PYR-1 19 2\. Objective 22 3\. Results 24 3.1 Degradation of benzo[a]pyrene by bacterial isolates from human skin 24 3.2 Toxification of polycyclic aromatic hydrocarbons by commensal bacteria from human skin 26 3.3 The Q-rich/PST domain of the AHR regulates both ligand induced nuclear transport and nucleocytoplasmic shuttling 28 4\. Discussion 47 4.1 Bacterial B[a]P degradation on the skin 47 4.1.1 Benzo[a]pyrene- degrading bacteria on the skin 48 4.1.2 Physiology and biochemistry of skin commensals and B[a]P degradation 50 4.2 Excretion of toxicologically relevant B[a]P metabolites on the skin. 52 4.2. 1 Identification of B[a]P metabolites 52 4.2. 2 Toxicological relevance of bacterial supernatants and identified B[a]P metabolites 54 4.3 The aryl hydrocarbon receptor (AHR) as the key enzyme for the metabolisation of PAHs in human cells 57 5\. Summary 62 6\. Zusammenfassung 64 7\. Literature 66 8\. List of Publications 89
Identification of Genomic Markers by RAPD-PCR Primer in Leukemia Patients

The aim of this study is to ascertain the possible application of Random Amplification of Polymorphic DNA (RAPD) analysis as a genetic test to investigate DNA polymorphisms and detection of genomic markers in various types of leukemia. The results showed unique profiles of amplified DNA fragments produced in genomic DNA of three types of leukemia by an arbitrary primer of decamer oligonucleotides OPA-09. The primer produced four types of amplified DNA fragments (980, 1659, 2187 and 3162 bp). The smallest amplified DNA fragment (980 bp) appeared in 14.3 and 13.3% of tested acute myeloid leukemia and chronic myeloid leukemia patients, respectively; but was absent in genomic DNA of chronic lymphoid leukemia and normal individuals. Whereas the largest amplified fragment (3162 bp) was present in 12.5, 20 and 75% of chronic lymphoid leukemia, chronic myeloid leukemia and normal individuals, respectively and was absent in acute myeloid leukemia. On the other hand, the two amplified fragments (1659 and 2187 bp) were present in normal and leukemia patients. Cluster analysis of amplified DNA fragments grouped the leukemia patients in two main groups. The detected DNA polymorphisms by the arbitrary primer OPA-09 might find application in developing efficient RAPD primer for diagnosis of leukemia.
Detecting Anomalies: The Relevance and Power of Standard Asset Pricing Tests

The two standard approaches for identifying capital market anomalies are cross-sectional coe cient tests, in the spirit of Fama and MacBeth (1973), and time-series intercept tests, in the spirit of Jensen (1968). A new signal can pass the rst test, which we label a score anomaly, it can pass the second test as a factor anomaly, or it can pass both. We demonstrate the relevance of each to a mean-variance optimizing investor facing simple transaction costs that are constant across stocks. For a risk-neutral investor facing transaction costs, only score anomalies are relevant. For a risk-averse investor facing no transaction costs, only factor anomalies are relevant. In the more general case of risk aversion and transaction costs, both tests matter. In extensions, we derive modi ed versions of the basic tests that net out anomaly execution costs for situations where the investor faces capital constraints, a multi-period portfolio choice problem, or transaction costs that vary across stocks. Next, we measure the econometric power of the two tests. The relative power of time-series factor tests falls with the in-sample Sharpe ratio of the incumbent factor model, as in Shanken (1992). New factor anomalies can be successively harder to detect, leading to a lower natural limit on the number of anomalies that can be identi ed by time series tests. Meanwhile, for an investor facing transaction costs, where score anomalies are also applicable, there can be a higher natural limit on the number of anomalies that can be statistically validated as relevant. ∗Contact: mbaker@hbs.edu. The authors thank participants at seminars at London Business School and the London School of Economics for helpful comments. Please do not quote without permission. The authors would like to thank Owen Lamont for helpful comments. Malcolm Baker is at the National Bureau of Economic Research and serves as a consultant to Acadian Asset Management, Patrick Luo was previously at Harvard Business School and is a data scientist at Farallon Capital Management, and Ryan Taliaferro is senior vice president at Acadian Asset Management. In addition, Malcolm Baker and Patrick Luo acknowledge support from the Division of Research at Harvard Business School. The views expressed herein are those of the authors and do not necessarily re ect the views of the National Bureau of Economic Research, Acadian Asset Management, or Farallon Capital Management. The views expressed herein should not be considered investment advice and do not constitute or form part of any o er to issue or sell, or any solicitation of any o er to subscribe or purchase, shares, units, or other interest in any particular investments.
Exploiting RASP Data Perturbation to BuildConfidential Query Services in the Cloud

With the advent of cloud computing technology, using clouds for hosting data query service has become increasingly popular because of the low cost of computation, hosting applications and content storage. As in cloud the data management and infrastructure management is provided by third-party security and privacy are the biggest concern. Until and unless data confidentiality and secure query processing are guaranteed it is always a risk for the data owner to move the sensitive data to the cloud. Workload must be reduced to fully realize the benefits of cloud computing. Therefore to meet the above said requirements RASP method is proposed where RASP stands for Random Space Perturbation. This data perturbation technique ensures that the data is not d istorted and does not lead to a security breach by allowing users to ascertain key summary information. Cloud computing enables outsourcing the management of the data related to individuals and organizations to a service provider as the hardware cost and t he maintenance cost is less. RASP provides exclusive security features for hosting query services in the cloud by satisfying the CPEL criteria where CPEL stands for data Confidentiality, query Privacy, Efficient query processing and Low working cost . KNN-R algorithm is used to process the range query and the KNN query. Here users have been authorized by the randomly generated product key value provided by the admin after successful registration followed by activation by admin thus maintaining confidentiality. User queries are retrieved within a very short span of time. Also analysed how the RASP method provides confidentiality of data and increases the working process of query.
Mean sediment residence time in barchan dunes

When a barchan dune migrates, the sediment trapped on its lee side is later mobilized when exposed on the stoss side. Then sand grains may undergo many dune turnover cycles before their ejection along the horns, but the amount of time a sand grain contributes to the dune morphodynamics remains unknown. To estimate such a residence time, we analyze sediment particle motions in steady state barchans by tracking individual cells of a 3‐D cellular automaton dune model. The overall sediment flux may be decomposed into advective and dispersive fluxes to estimate the relative contribution of the underlying physical processes to the barchan shape. The net lateral sediment transport from the center to the horns indicates that dispersion on the stoss slope is more efficient than the convergent sediment fluxes associated with avalanches on the lee slope. The combined effect of these two antagonistic dispersive processes restricts the lateral mixing of sediment particles in the central region of barchans. Then, for different flow strengths and dune sizes, we find that the mean residence time of sediment particles in barchans is equal to the surface of the central longitudinal dune slices divided by the input sand flux. We infer that this central slice contains most of the relevant information about barchan morphodynamics. Finally, we initiate a discussion about sediment transport and memory in the presence of bed forms using the advantages of the particle tracking technique.
Effects of precipitation on soil acid phosphatase activity in three successional forests in southern China

Phosphorus (P) is often a limiting nutrient for plant growth in tropical and subtropical forests. Global cli- mate change has led to alterations in precipitation in the re- cent years, which inevitably influences P cycling. Soil acid phosphatase plays a vital role in controlling P mineraliza- tion, and its activity reflects the capacity of organic P min- eralization potential in soils. In order to study the effects of precipitation on soil acid phosphatase activity, an experi- ment with precipitation treatments (no precipitation, natural precipitation and doubled precipitation) in three successional forests in southern China was carried out. The three forests include Masson pine forest (MPF), coniferous and broad- leaved mixed forest (MF) and monsoon evergreen broad- leaved forest (MEBF). Results showed that driven by season- ality of precipitation, changes in soil acid phosphatase activi- ties coincided with the seasonal climate pattern, with signifi- cantly higher values in the wet season than in the dry season. Soil acid phosphatase activities were closely linked to forest successional stages, with enhanced values in the later stages of forest succession. In the dry season, soil acid phosphatase activities in the three forests showed a rising trend with in- creasing precipitation treatments. In the wet season, soil acid phosphatase activity was depressed by no precipitation treat- ment in the three forests. However, doubled precipitation treatment exerted a significantly negative effect on it only in MEBF. These results indicate that the potential transforma- tion rate of organic P might be more dependent on water in the dry season than in the wet season. A decrease in organic P turnover would occur in the three forests if there was a drought in a whole year in the future. More rainfall in the wet season would also be adverse to organic P turnover in MEBF due to its high soil moisture.
Juggling with Proximity and Distance: Collaborative Innovation Projects in the Danish Cleantech Industry

abstract Studies increasingly apply a multidimensional proximity framework in the analysis of collaborations between actors. This article explores the influence of collaboration motives on the desired proximity characteristics of partnerships in innovation projects based on 50 interviews with representatives from Danish cleantech firms. How search criteria along proximity dimensions differ depends on the purposes of the collaborations. In this way, the analysis distinguishes between the types of collaboration, where geographical proximity is considered highly important and those where geographically distant partners are preferred. Geographical proximity plays an important role in partnerships motivated by interaction around actual product development and knowledge creation, while long-distance relationships appear to be important for partnerships motivated by market access and cost considerations. The insight that the desired proximity characteristics of partnerships are indeed contingent on the motive for collaborating highlights how the proximity framework can be applied in the analysis of firm decision making.
Graphene Oxide from Current Perspectives to Future Applications

In this paper, the development of graphene oxide for environmental applications, following the approaches of different research groups were studied. The results were grouped per three main lines, depollution behaviour and characteristics, novel sensors and sensor materials and toxicity associated with the use of those materials. The main results were of the research has been emphasized, and some perspectives were highlighted for the future in the conclusions. Graphene oxide took a huge leap forward, but in order to gain more knowledge, a unified perspective is still required from all research groups, an unified perspective concerning methods for testing and critical parameters which should not be missed in any depollution study. Graphene oxide has the potential to become a highly produced material, due to the many advantages it brings, as long as it does not add its toxicity and as long as the danger it removes is lesser than the danger we face from using it.
An Experimental Evaluation of Application Layer Protocols for the Internet of Things

The Internet of Things is envisaged to interconnect billions of devices, from sensors and actuators to smart objects, computers and vehicles. The main obstacle that arises is that technology should allow physical objects, usually constrained devices, to interact with applications. Therefore, already existing technologies and patterns should be adapted to the new requirements, or novel ones must be created. In this context, the application layer protocols play an important part in orchestrating an IoT network. This paper focuses on the comparison of different protocols by carrying out experiments and prototyping a real-world interaction between IoT network actors.
Switchable Multiband Monopole CRLH Antenna

─ In this paper, a switchable multiband monopole composite right/left-handed (CRLH) antenna is designed, fabricated and measured. The structure consists of a monopole loaded with three CRLH unit cells. By incorporating the three unit cells it aids in generating multiband frequencies. The switchable antenna is developed by placing the pin diodes which enables the simultaneous operation of unit cells. A detailed parametric study is done to investigate the influence and the effect of CRLH cells dimensions. The simulation and measured results are in good agreement. The results show multiple bands from 1-4 GHz. The measured maximum gain of antenna is 3.13 dBi. Index Terms ─ CRLH, metamaterials, monopole antenna, multiband, switchable.
Cross-Lingual Sentiment Analysis with Machine Translation Utility of training corpora and sentiment lexica

Recent advancements in machine translation foster an interest of its use in sentiment analysis. This thesis investigates prospects and limitations of using machine translation in cross-lingual sentiment analysis. To perform a sentiment analysis we need to learn linguistic features by either using tools such as part-of-speech taggers, parsers, or basic resources such as annotated corpora or sentiment lexica. We are motivated to study the translation of existing resources in English simply because building such tools and resources for each language requires considerable human effort. This severely limits the implementation of language specific sentiment analysis techniques similar to those developed for English. Labeled corpora and sentiment lexica are two main resources in the application of sentiment analysis. We translate them to a language with limited resources where we opt to focus on improving classification accuracy when (labeled or raw) training instances are available. In some cases, however, we may not have access to any training data. To address this scenario we explore methods to translate sentiment lexica to a target language as we also try to improve machine translation performance by generating additional context. For all experiments we work on English and Turkish data which consist of movie and product reviews and we perform two-class (positive-negative) classification -polarity detection in which we discard the neutral class. Consequently, we obtain promising results in polarity detection experiments where we use general-purpose classifiers trained on translated corpora while in this point we remark that dissimilarities between two corpora in different languages should be further studied for better integration of resources. We also find quantitative evidences to suggest that lexica translation is more troublesome since the inherit differences of expressing sentiment between two languages make it harder to preserve the sentiment of words/phrases when translating them from one language to another.