Miracle-dz/UniFAR-FTUs huggingface dataset:
Data protection and codes of conduct in collaborative research

ABSTRACT The article aims to describe the current status quo of codes of conduct applied by research institutions to manage data protection issues in light of the General Data Protection Regulation (GDPR). We assessed whether the current codes of conduct meet the criteria of codes of conduct as defined by Article 40 of the GDPR. We have found that there are very few ‘codes of conduct’ or good practices that would meet the definition set out in Article 40 of the GDPR. We have found that universities and research institutions had neither the incentives nor the resources to create internationally binding codes of conduct and settled for declarative documents or internal guidelines. A good level of compliance with the Data Protection Directive and national laws was adopted even without codes of conduct which would apply beyond a single institution or grant agency. We have identified that the demand and need for binding codes of conduct are increasing, albeit only in specific research fields. The main incentive is international cooperation, the need for the standardization of data protocols, and most likely fear of high sanctions introduced by GDPR.
Manufacture of Biogas from the Anaerobic Treatment of Cow Dung from Federal University of Technology, Owerri Livestock Farm

Energy from hydrocarbon compounds has over the years been expensive and also played a part in negative health implications amongst others, for this reason alternative sources of energy have been sort for. In the quest for a healthier, more cost-effective energy, cow dung as a renewable source has been proven to be very efficient. This study investigated the manufacture of biogas using cow dung from School of Agriculture and Agricultural Technology (S.A.A.T) livestock farm located in Federal University of Technology, Owerri, Imo State, Nigeria. 25 kg of the cow dung was used in this study. The digestion was carried out in a 50L anaerobic digester at a temperature of 30°C - 36°C and uncontrolled pH for a period of 40 days. The average quantity of biogas produced through the period was 10.39 liters, representing 46% of the total biogas production. The average temperature was 33.0°C. The utilization of cow dung as fuel will also help in the management of waste within the livestock farm. As an eco-friendly source of energy, the biomass generated after digestion can be utilized to improve soil fertility.
Managing staged policy implementation: Balancing short‐term needs and long‐term goals

Funding information National Health and Medical Research Council Abstract This study focuses on the agency of governments engaged in implementation processes that take place over a number of years and through multiple stages. The long timeframes associated with staged implementation leave reforms vulnerable to the institutional effects that may ultimately derail policy aspirations. Governments engaged in staged implementation need to be able to plan longitudinally (foresight capacity) and analyse whether implementation processes are creating endogenous sources of institutional change and the likely impact of such change (reflective capacity). In this paper, we argue that being able to exercise foresight capacity and reflective capacity is necessary but not sufficient, if long-term policy goals are to be realised. Governments must also be able to navigate the inconsistent objectives that arise across the different stages of an implementation process by modifying implementation approaches in ways that reduce the likelihood of unwanted implementation effects occurring—what we have labelled “mitigation capacity. ”
Geoenvironmental aspects of recycled materials in pavement applications: Leaching characterizations

Industrial byproducts, fly ash and steel slag are widely used in pavement subgrade soil stabilization. Similarly, recycled concrete aggregates (RCA) are one of the most commonly used waste materials in pavement base construction. These materials are known to leach heavy metals and other elements of environmental concerns. On the other hand, cement is frequently used as an activator during fly ash and slag stabilization, which considerably increases the material pH, and hence, the leaching potentials of toxic constituents. The pH of RCA greatly varies with age, source and storage conditions due to carbonation. Additionally, the influence of matric potential on the leaching behaviors of RCA remains unknown. This study investigated the leaching characteristics of RCA and cement activated fly ash and steel slag stabilized soils through laboratory batch water leach test, toxicity characteristic leaching procedure, synthetic precipitation leaching procedure and pH-dependent leach tests. The effluent concentrations of calcium (Ca), magnesium (Mg), aluminum (Al), barium (Ba), chromium (Cr), copper (Cu), iron (Fe), zinc (Zn), manganese (Mn), sulfur (S), dissolved inorganic/organic carbon (DIC/DOC), sulfate (SO4), pH, electrical conductivity (EC) and alkalinity were quantified. Moreover, geochemical modeling was performed to evaluate the leaching mechanisms of these elements. The effluent concentrations of Ca, Ba, Al, SO4 increased; Mg, Cu and DIC concentrations decreased; Fe, Zn and DOC fluctuated; and Cr and Mn concentrations remained unaffected by cement addition. Cement activation altered the pH dependent release of Ca, Cr, Ba, Zn, S, SO4, DIC and DOC, noticeably. Multiple batch tests were required for the comprehensive leaching assessment. Geochemical modeling indicated that, except for Cr, the releases of elements from cement activated fly ash and slag stabilized soils were solubility controlled. In case of RCA, leaching characteristics were considerably influenced by carbonation, particle sizes and liquid to solid ratios (L/S). Distinct pH dependent releases of
Coarse-to-fine Optimization for Speech Enhancement

In this paper, we propose the coarse-to-fine optimization for the task of speech enhancement. Cosine similarity loss [1] has proven to be an effective metric to measure similarity of speech signals. However, due to the large variance of the enhanced speech with even the same cosine similarity loss in high dimensional space, a deep neural network learnt with this loss might not be able to predict enhanced speech with good quality. Our coarse-to-fine strategy optimizes the cosine similarity loss for different granularities so that more constraints are added to the prediction from high dimension to relatively low dimension. In this way, the enhanced speech will better resemble the clean speech. Experimental results show the effectiveness of our proposed coarse-to-fine optimization in both discriminative models and generative models. Moreover, we apply the coarse-to-fine strategy to the adversarial loss in generative adversarial network (GAN) and propose dynamic perceptual loss, which dynamically computes the adversarial loss from coarse resolution to fine resolution. Dynamic perceptual loss further improves the accuracy and achieves state-of-the-art results compared with other generative models.
A brief overview of basic inference attacks and protection controls for statistical databases

With cyber-attacks on the dramatic rise in the recent years, the number of entities which realize the necessity of protecting their IT assets increases. Individuals are more aware of the potential threats and demand high level of security from the business entities having access to their personal and private data. Such entities have legal obligations to satisfy the confidentiality when processing sensitive data, but many fails to do so. Keeping the statistical data private is a challenge as the approach to the security breaches slightly differs from the classical understanding of data disclosure attacks. The statistical disclosure can be achieved using inference attacks on the not-effectively protected assets. Such attacks do not target the database access itself, i.e. are performed from a perspective of an internal user, but the statistical interface used to retrieve the statistical data from the database records. This paper sums up basic types of inference attacks classifying them in the CVSS standard and provides a series of fundamental countermeasures which can be undertaken to mitigate the risk of performing successful attack.
Dynamic Wedge Failure and Along‐Arc Variations of Tsunamigenesis in the Japan Trench Margin

Elastic dislocation models require large near‐trench slip to explain large tsunamigenesis, which is probably best exemplified in the 2011 M9 Tohoku earthquake. However, it is puzzling that the largest Tohoku tsunami heights occurred about 100 km north of the largest slip zone, where bathymetric surveys indicate no large slip at the trench or submarine landslides. Here we show that coseismic yielding of plentiful sediments in the northern Japan Trench margin can induce large inelastic uplift landward from the trench and diminish slip near the trench. The scarcity of sediments in the south leads to nearly elastic response with large slip at the trench and mostly horizontal seafloor displacement. Thus, the variations of sediments along the Japan Trench and sediment yielding can explain the puzzling variations of tsunamigenesis and near‐trench slip in this earthquake. Inelastic wedge deformation can be an important mechanism of tsunamigenesis in accretionary and other sediment‐filled plate margins.
Inferring Crustal Temperatures Beneath Italy From Joint Inversion of Receiver Functions and Surface Waves

Temperature distribution at depth is of key importance for characterizing the crust, defining its mechanical behavior and deformation. Temperature can be retrieved by heat flow measurements in boreholes that are sparse, shallow, and have limited reliability, especially in active and recently active areas. Laboratory data and thermodynamic modeling demonstrate that temperature exerts a strong control on the seismic properties of rocks, supporting the hypothesis that seismic data can be used to constrain the crustal thermal structure. We use Rayleigh wave dispersion curves and receiver functions, jointly inverted with a transdimensional Monte Carlo Markov Chain algorithm, to retrieve the VS and VP/VS within the crust in the Italian peninsula. The high values (>1.9) of VP/VS suggest the presence of filled‐fluid cracks in the middle and lower crust. Intracrustal discontinuities associated with large values of VP/VS are interpreted as the α−β quartz transition and used to estimate geothermal gradients. These are in agreement with the temperatures inferred from shear wave velocities and exhibit a behavior consistent with the known tectonic and geodynamic setting of the Italian peninsula. We argue that such methods, based on seismological observables, provide a viable alternative to heat flow measurements for inferring crustal thermal structure.
Patterns of oyster natural mortality in Chesapeake Bay, Maryland during 1991-2017 and its relationships with environmental factors and disease

Title of Thesis: PATTERNS OF OYSTER NATURAL MORTALITY IN CHEAPEAKE BAY, MARYLAND DURING 1991-2017 AND ITS RELATIONSHIPS WITH ENVIRONMENTAL FACTORS AND DISEASE Kathryn Leah Doering, Master of Science, 2019 Thesis Directed By: Professor Michael J. Wilberg, Marine Estuarine Environmental Sciences A common method of estimating natural mortality in bivalves includes several assumptions that are likely violated for oysters Crassostrea virginica in Chesapeake Bay, Maryland. In addition, while oyster disease dynamics are well studied spatially and temporally in the mid-Atlantic region, changes in disease-related relationships have not been investigated in Maryland. We developed a Bayesian estimator for natural mortality and applied it to oysters in Maryland. We then used the model output along with environmental factors and disease data to explore changes in the disease system over time. We found the largest differences in natural mortality estimates between the box count method and Bayesian model 1-3 years after a high mortality event. Some relationships changed over time in the disease system, most notably those associated with MSX, suggesting resistance to MSX has potentially developed. This work improves our estimates of natural mortality and understanding of oyster disease dynamics in Maryland. PATTERNS OF OYSTER NATURAL MORTALITY IN CHEAPEAKE BAY, MARYLAND DURING 1991-2017 AND ITS RELATIONSHIPS WITH ENVIRONMENTAL FACTORS AND DISEASE
Interhemispheric Asymmetry in Response of Low‐Latitude Ionosphere to Perturbation Electric Fields in the Main Phase of Geomagnetic Storms

Structures of sudden enhancements/depressions and associated interhemispheric asymmetry in low‐latitude total electron content (TEC) during the main phase (MP) of geomagnetic storms have remained unpredictable majorly due to oscillating equatorial vertical E×B drifts and resultant redistribution of plasma in low latitudes in a given seasonal background. Robust analysis of 7 major and 30 moderate ionospheric storms during the years 2000–2018 is performed with comprehensive literature review encompassing various sources of asymmetry in magnetosphere‐ionosphere coupling. Taking advantage of simultaneous long‐term observations of E×B drift from Jicamarca, H component from magnetometers, and global ionospheric map vertical TEC (VTEC) and TEC observations across the dip equator from the South American sector, simultaneous formation of peaks and valleys in VTEC and associated asymmetry are studied. Additionally, a three‐layer neural network‐based E×B drift model is developed using delta‐H observations that provide drift estimates in the absence of Jicamarca drifts. The main results establish simultaneous high‐magnitude short‐lived (1–2 hr) enhancements and depression in VTEC during the MP in daytime in both hemispheres with varying differences of −30 to 100 TECU with respect to quiet time mean and along with prominent existence of interhemispheric asymmetry in TEC during the MP regardless of seasons. Maximum VTEC in the northern and southern low latitudes is found to occur at different times during storms. Large difference of VTEC is found ranging between 10 and 30 TECU between the near conjugate locations of the hemispheres. Coincident global episodic peaks marked by steep VTEC falls show dominance of episodic eastward and westward penetration electric fields in the low‐latitude daytime ionosphere.
Observed El Niño‐La Niña Asymmetry in a Linear Model

Previous studies indicate an asymmetry in the amplitude and persistence of El Niño (EN) and La Niña (LN) events. We show that this observed EN‐LN asymmetry can be captured with a linear model driven by correlated additive and multiplicative (CAM) noise, without resorting to a deterministic nonlinear model. The model is derived from 1‐month lag statistics taken from monthly sea surface temperature (SST) data sets spanning the twentieth century, in an extension of an empirical‐dynamical technique called Linear Inverse Modeling. Our results suggest that noise amplitudes tend to be stronger for EN compared to LN events, which is sufficient to generate asymmetry in amplitude and also produces more persistent LN events on average. These results establish a null hypothesis for EN‐LN asymmetry and suggest that strong EN events may not be more predictable that what can be accounted for by a multivariate linear system driven by CAM noise.
Illegal Wildlife Trade: Scale, Processes, and Governance

Illegal wildlife trade (IWT) has increased in profile in recent years as a global policy issue, largely because of its association with declines in prominent internationally trafficked species. In this review, we explore the scale of IWT, associated threats to biodiversity, and appropriate responses to these threats. We discuss the historical development of IWT research and highlight the uncertainties that plague the evidence base, emphasizing the need for more systematic approaches to addressing evidence gaps in a way that minimizes the risk of unethical or counterproductive outcomes for wildlife and people. We highlight the need for evaluating interventions in order to learn, and the importance of sharing datasets and lessons learned. A more collaborative approach to linking IWT research, practice, and policy would better align public policy discourse and action with research evidence. This in turn would enable more effective policy making that contributes to reducing the threat to biodiversity that IWT represents.
Short-Term Wastewater Influent Prediction Based on Random Forests and Multi-Layer Perceptron

Influent flow rate is a crucial parameter closely related to the plant-wide control of wastewater treatment plants (WWTPs). In this study, a random forest (RF) model and a multi-layer perceptron (MLP) model are developed for hourly influent flow rate prediction at a confidential WWTP in Canada. Both models perform well on predicting influent flow rate one-step ahead. The coefficient of determination (R2) values of MLP and RF for the testing data set are 0.927 and 0.925, respectively. Furthermore, the multi-step ahead prediction accuracy of the proposed models is discussed. To improve the multi-step ahead prediction accuracy of the RF model, time-tag information is transformed to numerical values and then fed into the RF model as input. The R2 values of the RF model for the testing data set with and without time-tag information are 0.334 and 0.811, respectively. The results show that the RF model’s performance for multi- step ahead prediction is heavily affected by the time-tag information. Including time-tag information as input could dramatically improve the multi-step ahead prediction accuracy. In this study, the RF model shows more robust performance than the MLP model on solving short-term wastewater influent prediction problems. Influent flow rate is a crucial parameter closely related to the plant-wide control of wastewater treatment plants (WWTPs). In this study, a random forest (RF) model and a multi-layer perceptron (MLP) model are developed for hourly influent flow rate prediction at a confidential WWTP in Canada. Both models perform well on predicting influent flow rate one-step ahead. The coefficient of determination (R2) values of MLP and RF for the testing data set are 0.927 and 0.925, respectively. Furthermore, the multi-step ahead prediction accuracy of the proposed models is discussed. To improve the multi-step ahead prediction accuracy of the RF model, time-tag information is transformed to numerical values and then fed into the RF model as input. The R2 values of the RF model for the testing data set with and without time-tag information are 0.334 and 0.811, respectively. The results show that the RF model’s performance for multi-step ahead prediction is heavily affected by the time-tag information. Including time-tag information as input could dramatically improve the multi-step ahead prediction accuracy. In this study, the RF model shows more robust performance than the MLP model on solving short-term wastewater influent prediction problems.
Towards the development of a knowledge management practices survey for application in knowledge intensive organisations

Various surveys of Knowledge Management Practices (KMPs) in private firms show how an increasing awareness of Knowledge Management (KM) is a critical determinant of an organisation’s competitiveness. While private sector strategies favouring internal knowledge sharing and external knowledge protection often provide strategic advantage, public sector research organisations such as South Africa’s science councils operate in an environment where, for reasons of wider public interest, transparency is encouraged and knowledge is rendered widely accessible. Unfortunately, however, little has been done to develop rigorous measurements of KMPs in such knowledge intensive organisations (KIOs) that primarily engage in knowledge intensive service activities. To complicate matters further, the majority of studies have been inter-organisational and multi-sectoral, focusing on large organisations in the private sector. Few studies have measured perceptions of KMPs amongst employees of a single organisation and even fewer have focused on KMPs within the public sector. This paper will discuss the theoretical and methodological approach used in the development of a survey aimed at measuring employee perceptions of KMPs within the Human Sciences Research Council (HSRC), one of South Africa’s largest public KIOs dedicated to ‘social science research that makes a difference. ’ Principal component analysis of the survey data revealed six factors or constructs applicable to the measurement of KMPs. The results validate the survey instrument and offer a contribution toward the development of a KMP measurement instrument that may be applied across other KIOs in South Africa.
RANCANGAN PEMBELAJARAN ILMU TAJWID BERBASIS MULTI MEDIA UNTUK SISWA TINGKAT DASAR PADA TAMAN PENDIDIKAN AL-QUR’AN DTA AT-TAQWA

Understanding of religion should be done by parents from since childhood, at which time the child can easily absorb knowledge, but how that is done to convey that knowledge should be done with the right method to facilitate the child understand. The method has been used in Islamic religious learning in particular subjects, al-Qur'an in Al-Qur'an garden diniyah education, ta'miliyah and awaliyah (DTA) at-Taqwa is a writer doing research lecture method, the learning method less attractive for the students, so that the level of their understanding of the material is less, it can be seen from the daily repetition of the material al-Qur'an student base level DTA is lower compared to other subject matter. To overcome these problems, needed a fun but learning methods can be understood easily. In this case we can use interactive multimedia. Learning with interactive multimedia, is expected to improve students' learning motivation, increase comprehension faster than just read, can facilitate the process of learning and teaching activities at the Garden Education Qur'an diniyah, ta'miliyah, awaliyah (DTA) At-Taqwa . Learning with multimedia applications using already testing by whitebox and black box testing, the test results can be concluded that the system that has made the program is already running in accordance with the purpose of planning.
Live Blogging and Social Media Curation: Challenges and Opportunities for Journalism

Blogging and social media’s contribution to a realignment of the relationship between journalists and their audiences is discussed by Einar Thorsen in Live Blogging and Social Media Curation. Journalists are facing challenges to preserve traditional standards, such as verification of information and sources, whilst also capitalising on the opportunities afforded by the immediacy, transparency and interactive nature of online communication. Thorsen analyses these issues through two case studies: one focuses on ‘live’ blogging and elections, and a second looks at the role of social media in the Arab Spring. He demonstrates how journalists face new challenges in relation to social media curation, whilst the emergent forms and practices also present a wealth of opportunities.