Miracle-dz/UniFAR-FTUs huggingface dataset:
Who Gets a Second Chance? Effectiveness and Equity in Supervision of Criminal Offenders*

Most convicted offenders serve their sentences under “community supervision” at home instead of in prison. Under supervision, however, a technical rule violation, such as not paying fees, can result in incarceration. Rule violations account for 25% of prison admissions nationally and are significantly more common among black offenders. I test whether technical rules are effective tools for identifying likely reoffenders and deterring crime and examine their disparate racial impacts using administrative data from North Carolina. Analysis of a 2011 reform reducing prison punishments for technical violations on probation reveals that 40% of rule breakers would go on to commit crimes if spared harsh punishment. The same reform also closed a 33% black-white gap in incarceration rates without substantially increasing the black-white reoffending gap. These effects combined imply that technical rules target riskier probationers overall but disproportionately affect low-risk black offenders. To justify black probationers’ higher violation rate on efficiency grounds, their crimes must be roughly twice as socially costly as that of white probationers. Exploiting the repeat spell nature of the North Carolina data, I estimate a semiparametric competing risks model that allows me to distinguish the effects of particular types of technical rules from unobserved probationer heterogeneity. Rules related to the payment of fees and fines, which are common in many states, are ineffective in tagging likely reoffenders and drive differential effects by race. These findings illustrate the potentially large influence of ostensibly race-neutral policies on racial disparities in the justice system.
The link between post-implementation learning motivation and enterprise resource planning system usage: a pilot study

This study develops a conceptual model of the relationship between post implementation learning and enterprise resource planning system (ERP) usage. It equally proposes perceived usefulness, perceived ease-of-use and mastery-goal orientation as the dimensions of post implementation learning motivation. A pilot study and comprehensive review of the literature on enterprise systems and information usage was conducted in this study. Based on the suggested relationships between the cognitive dimensions of post-implementation motivation and ERP system usage, a reliability test of the internal consistency of the proposed measurement instruments was validated by a pilot test
Evaluation of the Quality of Microphone Array Enhanced Speech

Microphone arrays offer the possibility of hands free speech acquisition. This increases the convenience for those using speech technologies as they do not need to hold a microphone in order to interact with a speech system. In addition, a microphone array also has the advantage of potential gains in signal-tonoise ratio in noisy and reverberant environments. In this paper we evaluate the quality of a locally designed four element linear microphone array. The microphone array enhanced speech is evaluated on distortion, noise and speaker identification performance. The reported results show the noise canceling beamformer with post filter as having produced low distortion, high signal-tonoise ratio speech and the best speaker identification rate when compared to other general beamforming techniques.
Predicting Academy Award Winners Using Discrete Choice Modeling

Every year since 1928, the Academy of Motion Picture Arts and Sciences has recognized outstanding achievement in film with their prestigious Academy Award, or Oscar. Before the winners in various categories are announced, there is intense media and public interest in predicting who will come away from the awards ceremony with a golden Oscar statuette. There are no end of pet theories about which nominees are most likely to win, based on observations such as the fact that only three movies have won the Best Picture Oscar without also receiving a Best Director nomination. Despite this, there continue to be major surprises when the winners are announced. This article frames the question of predicting the four major awards—picture, director, actor in a leading role, actress in a leading role—as a discrete choice problem. Using Bayesian modeling techniques, it is possible to predict the winners in these four categories with a reasonable degree of success. The analysis also reveals which past nominees have really upset the odds (winners with low estimated probability of winning), and which appear to have been truly robbed (losers with high estimated probability of winning).
Environmental DNA for detecting
 Bulinus truncatus
 : A new environmental surveillance tool for schistosomiasis emergence risk assessment

Under ongoing climate changes, the development of large-scale monitoring tools for assessing the risk of disease emergence constitutes an urging challenge. This is particularly the case for snail-borne diseases such as the urogenital bilharziasis that emerged in Corsica and threat European countries. The expansion of this tropical disease mainly relies on the local presence of competent snail hosts such as Bulinus truncatus . Unfortunately, very little is known about the actual repartition of freshwater snails worldwide which makes new emergences difficult to predict. In this study, we developed two ready-to-use environmental DNA-based methods for assessing the distribution of B. truncatus from water samples collected in the field. We used two approaches, a quantitative PCR (qPCR) and a droplet digital PCR (ddPCR) approach. We successfully detected B. truncatus in natural environments where the snail was previously visually reported. Our environmental DNA diagnostic methods showed a high sensitivity (≈60 DNA copy per mL of filtered water) and a high specificity to B. truncatus . Results obtained in qPCR and ddPCR were very similar. This study dem-onstrates that environmental DNA diagnostics tools enable a sensitive large-scale monitoring of snail-borne diseases hence allowing the delimitation of areas potentially threatened by urogenital schistosomiasis.
Review on the Status of Theory and Research of Social Media Studies in Malaysia: A Conceptual Paper

In the recent years, the literature indicated that adoption and consequences of using social media on the users and society has become a popular topic among the communication scholars. However, past studies also show that prior efforts in discussing on the stature and scholarship of social media research in Malaysia is scarce. Thus, the purpose of this conceptual paper is to review on the theoretical patterns and research trends of social media related studies on Malaysian users. In particular, the method used is based on literature reviews in chronological order concerning new media, social media and research trends analyses from journal articles, theses proceedings and conferences, book and more. A framework of analysis was generated to identify the frequency and occurrences in theoretical application, research topic areas, methodological approaches, types of contents, social media medium of interest and research developmental phases of social media studies. The study ends with summaries and recommendations to utilise comprehensive content analyses of communication and media journals in Malaysia to trace the theoretical trends and research patterns pertaining to social media research.
E cient Linear Fusion of Partial Estimators

Many signal processing applications require performing statistical inference on large datasets, where computational and/or memory restrictions become an issue. In this big data setting, computing an exact global centralized estimator is often either unfeasible or impractical. Hence, several authors have considered distributed inference approaches, where the data are divided among multiple workers (cores, machines or a combination of both). The computations are then performed in parallel and the resulting partial estimators are finally combined to approximate the intractable global estimator. In this paper, we focus on the scenario where no communication exists among the workers, deriving e cient linear fusion rules for the combination of the distributed estimators. Both a constrained optimization perspective and a Bayesian approach (based on the Bernstein-von Mises theorem and the asymptotic normality of the estimators) are provided for the derivation of the proposed linear fusion rules. We concentrate on finding the minimum mean squared error (MMSE) global estimator, but the developed framework is very general and can be used to combine any type of unbiased partial estimators (not necessarily MMSE partial estimators). Numerical results show the good performance of the algorithms developed, both in problems where analytical expressions can be obtained for the partial estima⇤Corresponding author: David Luengo Email addresses: david.luengo@upm.es (David Luengo), luca.martino@uv.es (Luca Martino), victor.elvira@telecom-lille.fr (Vı́ctor Elvira), monica.bugallo@stonybrook.edu (Mónica Bugallo) Preprint submitted to Digital Signal Processing November 2, 2017 tors, and in a wireless sensor network localization problem where Monte Carlo methods are used to approximate the partial estimators.
Relating electrified cloud properties to Wilson currents: an oceanic and continental case study

Thunderstorms and other electrified, non-lightning producing clouds are thought to play an important role in maintaining the potential difference between Earth’s surface and upper atmosphere. These clouds are responsible for producing Wilson currents between cloud tops in the troposphere and the electrosphere which help sustain the Global Electric Circuit (GEC). Estimates of Wilson currents for oceanic and continental electrified clouds were recently derived from data collected over two decades during multiple field campaigns involving the NASA ER-2 aircraft. It was found that the strength of Wilson currents varies by storm type and, on average, is higher for oceanic storms than their continental counterparts. This study builds upon findings made from the ER-2 data set and investigates relationships between the dynamical and microphysical properties of electrified clouds alongside their ER-2 Wilson current estimates. Variations of these properties were also studied during the lifecycles of one oceanic and two continental storms from 19 September 2001. Maximum reflectivity measured by the Next Generation Radar (NEXRAD) and ER-2 Doppler radars, along with radar derived precipitation ice mass and ice water path, updraft volume, maximum updraft velocity and echo top height were compared to the Wilson current estimates. Some cloud properties, such as ice water path and updraft volume, correlated well to the Wilson currents. Cloud top heights, however, did not have such a strong correlation. Further research is needed to determine if these results are robust. If proven, they could be utilized as Wilson current parameterizations in a modeling framework of the GEC.
On the Necessity of Graph Kernel Baselines

Naturally, graph structured data is not easy to learn from. As opposed to itemsets which can be represented by a table of fixed length, there is no obvious representation language for graphs which allows for an easy similarity measure in order to perform e.g. classification tasks on sets of graphs. There have been introduced numerous graph kernels which tackle the problem of defining a suitable similarity between graphs by incorporating structural information. In this article, however, we revert to the very simplistic approach which is to regard a graph as a (multi) itemset made up of node and edge labels. We consider our method as a baseline and compare it to several established graph kernels on a wide range of benchmark datasets. Our observations suggest that for the overwhelming number of available datasets, actually utilizing the graphs’ structure in graph kernels does not significantly improve the classification accuracy.
Charles Darwin University Examination of the Relationship between Servant Leadership and Agency Problems Gender Matters Politis, John; Politis, Denis

Purpose – The paper examines the relationship between servant leadership and agency problems. Also, it seeks to determine whether gender plays a role in this relationship. Design/methodology/approach A survey of 276 employees was carried out to investigate the relationship between the characteristics of servant leadership and the constructs of agency problems of thirty six male and twenty two female managers/supervisors in the banking sector months before the financial crisis in Cyprus. The responses were subjected to a series of correlational and structural equation modelling analyses. Findings – The study revealed three major findings. Firstly, the relationship between servant leadership behaviour and agency problems is near zero and not significant. Secondly, the servant leadership behaviour of female managers/supervisors brings the desired negative influence on the constructs of agency problems. Finally, the servant leadership behaviour of males has a more positive and significant influence on agency problems than that of females. These findings should be interpreted with caution, because more female than male participants rated the male managers/supervisors, and salient traits might cause followers to feel that female managers display more servant leadership characteristics, regardless of whether they exhibit them or not. Research limitations/implications – The conclusions cannot be generalised because the research was conducted in a country undergoing a financial crisis. However, this study provides a springboard to further explore whether the findings are valid if the sample is taken from a country not facing financial crisis, and if an equal number of male and female participants involved in rating male managers/supervisors. Practical implications – These findings provide evidence that servant leadership is not a genderneutral ethical construct, and practitioners should focus to develop or recruit managers who possess an ethic of care that could bring the desired negative outcome on the constructs of agency problems. Originality/value – This is the first study empirically investigating the agency problems – ethical leadership relationship in Cyprus. Moreover, the potential role played by gender for the aforementioned relationship was empirically examined.
An Application Placement Technique for Concurrent IoT Applications in Edge and Fog Computing Environments

Fog/Edge computing emerges as a novel computing paradigm that harnesses resources in the proximity of the Internet of Things (IoT) devices so that, alongside with the cloud servers, provide services in a timely manner. However, due to the ever-increasing growth of IoT devices with resource-hungry applications, fog/edge servers with limited resources cannot efficiently satisfy the requirements of the IoT applications. Therefore, the application placement in the fog/edge computing environment, in which several distributed fog/edge servers and centralized cloud servers are available, is a challenging issue. In this article, we propose a weighted cost model to minimize the execution time and energy consumption of IoT applications, in a computing environment with multiple IoT devices, multiple fog/edge servers and cloud servers. Besides, a new application placement technique based on the Memetic Algorithm is proposed to make batch application placement decision for concurrent IoT applications. Due to the heterogeneity of IoT applications, we also propose a lightweight pre-scheduling algorithm to maximize the number of parallel tasks for the concurrent execution. The performance results demonstrate that our technique significantly improves the weighted cost of IoT applications up to 65 percent in comparison to its counterparts.
Linking Governance and Management Perspectives with Conservation Success in Protected Areas and Biosphere Reserves

The implementation of protected areas that effectively meet their conservation objectives is one of the principal challenges in the endeavour to halt biodiversity loss. Though more than 100,000 protected areas cover about ten percent of the Earth’s terrestrial surface today, their success often leaves a great deal of room for improvement when regarded from the viewpoint of conservation. The overall objective of the interdisciplinary GoBi (Governance of Biodiversity) Research Group is to identify and assess the success and failure factors of protected areas with a focus on biosphere reserves. This serves the higher-level goal of advancing empirical knowledge and conceptual understanding of the results of the establishment of protected areas. We are integrating ecological and socioeconomic data in order to identify typical profiles of sets of variables influencing conservation success in protected areas. Typical research questions are, for example: What are the principal factors influencing the effective functioning of protected areas? How do they work? And how are they connected? We specifically scrutinize governance and management approaches because we believe that they are the key to the success of protected areas but have not yet received the attention they appear to warrant. Also, contrary to other factors influencing the success of protected areas, e.g., invasive species, changes in climate or macro-pressures on resources, governance and management approaches can be relatively easily controlled by those intending to implement PAs. This paper gives an overview over the challenges protected areas are facing in their endeavour to achieve conservation success. Subsequently, GoBi’s approach to examining the determinants of conservation success and their relative importance is discussed, and initial theoretical and empirical findings are presented. The Authors – Interdisciplinary Perspectives Susanne Stoll-Kleemann, the leader of the GoBi Research Group, is a Geographer by training, with a focus on Sustainability Science. The other authors are (associated) members of the GoBi Research Group: Svane Bender did her studies in Landscape Ecology with a strong interest in international aspects. Augustin Berghöfer`s background is in Economics and Political Science. Monika Bertzky was trained in Biology with a focus on Tropical Ecology. Nadine Fritz-Vietta holds a double degree in International Business as well as in Wildlife Management. Rainer Schliep did his university degree in Landscape Planning. Barbara Thierfelder holds a diploma in Geography and is a trained facilitator. The authors thank Sascha Maier for his ongoing and unfailing support within the GoBi Research Group.
Carbon nanotube electronics for IoT sensors

The Internet of Things (IoT) is the concept of a ubiquitous computing ecosystem inwhich electronics of custom form factors are seamlessly embedded into everyday objects. At the heart of the IoT are electronic sensors capable of detecting physical/environmental phenomena, translating these measurements into electrical signals, andwirelessly transmitting the data for remote computing. Critical to the development of IoT sensors and systems are low-costmaterials, robust enough to sustain stable electrical performance overmedium to long periods of time, yet sensitive enough to detect small changes in the surrounding environment. Suchmaterials should bemechanically flexible and amenable to solution-based processing to facilitate large scale productionmethods, such as rollto-roll printing. Carbon nanotubes (CNTs) are one of the leadingmaterial candidates to satisfy these requirements because of their unique electrical andmechanical properties, which enable robust and versatile devices, in combinationwith their chemical properties, which allow for the processing of CNTs from solution. These advantages have enabled demonstration of amyriad of printedCNTbased electronics and sensors on diverse substrates withwide ranges of functionality, spanning from simple sensors based on passive devices to complexmulti-stage circuitry and display electronics. In this review, we provide a comprehensive summary of the CNT-based electronics and sensor space with an emphasis on applications alignedwith the IoT. Primary coverage is devoted to devices consisting of randomly orientedCNTnetworks; however, the advantages and capabilities of singlenanotube devices will also be discussed. Keyworks across various types of sensors will be reviewed and a summary of the remaining challenges for CNT-based sensor technologies will be presented.
Image Retrieval based on Macro Regions

Various image retrieval methods are derived using local features, and among them the local binary pattern (LBP) approach is very famous. The basic disadvantage of these methods is they completely fail in representing features derived from large or macro structures or regions, which are very much essential to represent natural images. To address this multi block LBP are proposed in the literature. The other disadvantage of LBP and LTP based methods are they derive a coded image which ranges 0 to 255 and 0 to 3561 respectively. If one wants to integrate the structural texture features by deriving grey level co-occurrence matrix (GLCM), then GLCM ranges from 256 x 256 and 3562 x 3562 in case of LBP and LTP respectively.
Comparison of four different obstacle models of fluid flow with a slip-like boundary condition

In this paper, we investigate a time-discretized 2-dimensional Navier-Stokes equation with a slip-like boundary condition, which arises in the melting ice problem with obstacle. We study the existence and uniqueness of a approximate solution. We also study the numerical solution of melting ice problem using Continuous Galerkin method.
Key Determinants of Enterprise E-banking Assimilation

This paper empirically examines key determinants of enterprise e-banking assimilation. The analytical results unveil that utilitarian value and usability positively affect trustworthiness and satisfaction of enterprise e-banking services. In particular, firms’ satisfaction possesses a significant mediating effect on continuance intention to use enterprise e-banking services in business operations. The present study makes contributes to research and practice. The empirical findings enrich the understanding of enterprise e-banking assimilation and have managerial implications for the development of enterprise e-banking systems and services.
GROWTH, YIELD, AND YIELD COMPONENT CHANGES IN RESPONSE TO METHANOL APPLICATION ON RICE (ORYZA SATIVA CV. SHIROUDI)

In order to study the effects of methanol foliar application on growth analysis on rice, an experiment was performed using completely randomized block design in 3 replications at Rice Research Station in Tonekabon, north of Iran, during 2012 growing season. Aqueous solutions were 0%, 6%, 12%, 18% and 24% (v/v) methanol. Methanol solutions were sprayed three times on foliage parts of rice with two week intervals (45 days after transplanting). The results from these experiments indicated that, in general, methanol did not affect on growth and yield in rice and therefore, seem to be ineffective as a growth enhancer and foliar sprays of aqueous methanol cannot be recommended for rice. Also, there was no significant difference among four levels of methanol application and control in the growth indices. Keyword: Rice, Methanol, Yield, Total Dry Matter, Leaf Area Index
Sovereign Credit Ratings under Fiscal Uncertainty

This paper studies the response of credit rating agencies to an increase in uncertainty about a government's fiscal position. To that end, a measure of the uncertainty around official forecasts of the public budget deficit is constructed that is comparable across time and a range of advanced economies. To estimate the effect of fiscal uncertainty on sovereign credit ratings, an empirical framework is developed that accounts for the high stability of ratings over time. Results suggest that fiscal uncertainty increases the predictive power of a model of rating changes and can explain why sovereign ratings are often changed more frequently during crises.