Miracle-dz/UniFAR-FTUs huggingface dataset:
Ethnicity, Democratisation and Decentralization in Ethiopia: The Case of Oromia

The 20th century has been shaped by class and national struggles intended to end the asymmetrical relations that arose in the historical process of the creation of the multi-ethnic polity of Ethiopia. This study explores and assesses the democratization and decentralization experiment in Ethiopia. It focuses on the Oromia region, which is the country's largest region as well as housing its single largest ethnic group. It describes the demand of the Oromo people for self-rule and democratic governance on the one hand, and the promises made on paper by the government in power, on the other. It concludes that the Oromia region is a classical case in terms of the degree of failure of the regime's policies on the national question and the continued struggle for real autonomy and democracy on the part of the local population.
A Bayesian View of Boosting and Its Extension

In this paper, we provide a Bayesian perspective of boosting framework, which we refer to as Bayesian Integration. Through this perspective, we prove the standard ADABOOST is a special case of the naive Bayesian tree with a mapped conditional probability table and a particular weighting schema. Based on this perspective, we introduce a new algorithmADABOOST.BAYES by taking the dependency between the weak classifiers into account, which extends the boosting framework into non-linear combinations of weak classifiers. Compared with standard ADABOOST, ADABOOST.BAYES requires less training iterations but exhibits stronger tendency to overfit. To leverage on both ADABOOST and ADABOOST.BAYES, we introduce a simple switching schema ADABOOST.SOFTBAYES to integrateADABOOST and ADABOOST.BAYES. Experiments on synthetic data and the UCI data set prove the validity of our framework.
Structural and electronic properties of Fe 3+ and Fe 2+ centers in GaN from optical and EPR experiments

This work provides a consistent picture of the structural, optical, and electronic properties of Fe-doped GaN. A set of high-quality GaN crystals doped with Fe at concentrations ranging from 5 1017 cm−3 to 2 1020 cm−3 is systematically investigated by means of electron paramagnetic resonance and various optical techniques. Fe3+ is shown to be a stable charge state at concentrations from 1 1018 cm−3. The fine structure of its midgap states is successfully established, including an effective-mass-like state consisting of a hole bound to Fe2+ with a binding energy of 50±10 meV. A major excitation mechanism of the Fe3+ T1→ A1 luminescence is identified to be the capture of free holes by Fe2+ centers. The holes are generated in a two-step process via the intrinsic defects involved in the yellow luminescence. The Fe3+/2+ charge-transfer level is found 2.863±0.005 eV above the valence band, suggesting that the internal reference rule does not hold for the prediction of band offsets of heterojunctions between GaN and other III-V materials. The Fe2+ E→ T2 transition is observed around 390 meV at any studied Fe concentration by means of Fourier transform infrared spectroscopy. Charge-transfer processes and the effective-mass-like state involving both Fe2+ states are observed. At Fe concentrations from 1 1019 cm−3, additional lines occur in electron paramagnetic resonance and photoluminescence spectra which are attributed to defect complexes involving Fe3+. With increasing Fe concentration, the Fermi level is shown to move from near the conduction band to the Fe3+/2+ charge-transfer level, where it stays pinned for concentrations from 1 1019 cm−3. Contrary to cubic II-VI and III-V materials, both electronic states are effected by only a weak Jahn-Teller interaction.
Mind the Gap: An Annotated Overview of Datasets in the Study of Institutions and Conflict in Divided Societies

This paper engages in a systematic overview of the existing datasets on institutions, conflict and peace, as well as divisions and diversity. This overview indicates that an enormous amount of data is unevenly distributed across different issue areas. There is a lack of data capturing specific sets of political institutions (e.g., centripetalism), dynamic changes in a country’s relational demographics across identity groups, the ethnicization of political institutions (especially in the security sector), and security sector reform. Many datasets suffer from missing data and an alarming dearth of transparency. Our paper concludes with suggestions for yet unexplored research questions and avenues for further data collection.
Soundscape analysis by means of a neural network-based acoustic summary

The importance of detecting and characterizing sound events in the context of soundscape analysis is more and more understood among acousticians, architects and urban planners. A compilation of typical sounds for a given location, supplemented with a selection of rare but salient sound events, can quickly and efficiently provide an overview of the specific soundscape. The main subject of this paper is to construct a computational model to automatically create such an acoustic summary, using a biologically inspired auditory processing model. In particular, a neural network approach is taken, using a self-organizing map (also called a Kohonen map). A series of psychoacoustic features extracted from the sound forms the input data of the model at each time step. Typically, the learning algorithm of self-organizing maps is strictly dependent on the frequency of occurrence of the input data. However, human perception and retrospective assessment of soundscapes depend on more than only the rate of occurrence of particular sounds. For example, salient events will be remembered more vividly, even if they occur only rarely. To take into account this effect, a specific unsupervised continuous learning algorithm is used, which promotes memorizing less often occurring sounds too. At the end of training, the self-organized map represents an exhaustive acoustic summary of the soundscape at a particular location, and can be used to retrieve and listen to particular sound events.
Topoclimatic Zones and Ice Dynamics in the Caves of the Northern Yukon, Canada

In the upper basin of the Porcupine River, the subhorizontal caves of Bear Cave and Tsi-it-toh-Choh mountains are characterized by a very rich ice zone. The authors propose a model for the build-up of ice based on the formation of hexagonal ice sublimation crystals on the cold walls of underground passages. In this model, water freezes and thaws many times, causing a series of different forms from the ceiling to the floor of the caves. This process will sometimes provoke total obstruction of a passage due to particular topoclimatic conditions or a change of climate, notably an increase in atmospheric humidity. During the summer the passage where the ice is located is preceded by a warm and humid passage and is followed by a cold and extremely dry passage, in which are preserved fragments of wood, animal faeces and remains of small mammals. Key words: Yukon, Porcupine River, Bear Cave and Tsi-it-toh-Choh mountains, caves, climate, cave ice
Modeling Item-Level Data With Item Response Theory

ficult questions. Ideally, the two camps should have much cross fertilization, and the lines between them should be blurred. However, complex theories are often con structed before appropriate meth ods are developed for testing the hypotheses. Additionally, quanti tative psychologists often develop techniques that might be difficult and impractical to apply initially to real-data problems. These novel techniques need to be refined through robustness studies and analytical work before they can be used with real-world data. A psy chometric framework called item response theory (IRT) has under gone such prudent testing and re finement and is now ready to be implemented into the mainstream of psychological research and prac tice. IRT has already had a major impact on educational testing through its impact on computer ized adaptive testing (CAT). The precision of IRT-based item statis tics allows computerized testing programs to choose items that pro vide maximum psychometric in formation for an individual exam
Bayesian Nonparametric Modeling for Rapid Design of Metamaterial Microstructures

We consider the problem of rapid design of massive metamaterial (MTM) microstructures from a statistical point of view. A Bayesian nonparametric model, namely, Gaussian Process (GP) mixture, is developed to generate the mapping relationship from the microstructure’s geometric dimension to the electromagnetic response, which is approximately expressed in a closed form of Drude-Lorentz type model. This GP mixture model is neatly able to tackle nonstationarity, discontinuities in the mapping function. The inference is performed using a Markov chain relying on Gibbs sampling. Experimental results demonstrate that the proposed approach is highly efficient in facilitating rapid design of MTM with accuracy.
Meteorological Impacts of Forest Mortality due to Insect Infestation in Colorado

AbstractPhysical characteristics of forests and other ecosystems control land–atmosphere exchanges of water and energy and partly dictate local and regional meteorology. Insect infestation and resulting forest dieback can alter these characteristics and, further, modify land–atmosphere exchanges. In the past decade, insect infestation has led to large-scale forest mortality in western North America. This study uses a high-resolution mesoscale meteorological model coupled with a detailed land surface model to investigate the sensitivity of near-surface variables to insect-related forest mortality. The inclusion of this land surface disturbance in the model increased in simulated skin temperature by as much as 2.1 K. The modeled 2-m temperature increased an average of 1 K relative to the default simulations. A latent to sensible heat flux shift with a magnitude of 10%–15% of the available energy in the forested ecosystem was predicted after the inclusion of insect infestation and forest dieback. Although re.
The First-Year Gateway Experience: A Groundbreaking Model

Based on calls for a paradigm shift in higher education, which have appeared in the literature for years (Barr &Tagg, 1995; Tagg, 2003, Bryant University transformed its first-year experience into an innovative model, The First-Year Gateway). Informed by research from The Carnegie Foundation for the Advancement of Teaching’s Rethinking Undergraduate Business Education, the Association of American Colleges & Universities’ Liberal Education for America’s Promise, and the Wabash National Study, a group identified five learning outcomes: effective communication, critical thinking, ethical reasoning, diversity awareness, and information literacy. Key to this undertaking was faculty development, and utilizing assessment data to improve curricular design and learning outcomes. The result is an interdisciplinary 13 credit first-year program developed to foster a successful transition into Bryant University. Launched in fall 2012, assessment data was gathered to determine whether common learning outcomes were achieved. Faculty embedded student success goals into their courses, which are designed to foster purposeful adjustment to higher education. Preliminary assessment indicates institutional gains in retention, academic standing, and student and faculty engagement during the implementation year. The new model, based on Wenger’s community of practice (COP), created opportunities to discuss pedagogy. Most importantly, the model fostered faculty’s deeper understanding of first-year transitions.
Diurnal Time Budgets and Activity Rhythm of the Asiatic Wild ass Equus hemionus in Xinjiang, Western China

Studies on time budgets have shown that four factors may influence the daily activity budgets of the Asiatic wild ass: a) seasonal change of forage biomass and quality; b) diurnal and seasonal temperature variations; c) livestock movements and human activity; d) circadian period. In order to test these factors, the diurnal time budgets of the Asiatic wild ass was studied using the focal sampling method in Xinjiang Province (China) during 2007. According to our results, all four factors influenced the diurnal time budgets of Asiatic wild ass, which spent more than 45% (up to 66.77%) of their daytime feeding on pastures, and about one third resting (26.21%-38.06%) across all seasons. Moving, vigilance and "other" activities only made up less than 9% of the activity budgets in the most daytime of a year. Asiatic wild ass showed bimodal feeding activity in most seasons, but with longer daytime resting periods during hot months. In summer, especially during the rut, Asiatic wild ass devoted more significant time to "other" activities (suckling, moving, courting and agonistic behavior). However, the percentage of time for these activities was still notably lower than feeding and resting.
Integrated View of Inter-Firm Cooperation: An Empirical Study in Tourism Region

Many studies have tried to explain the inter-firm relationship especially inter-firm cooperation. However, among them, the role of social influence has gotten little empirical investigation or to be neglected. Using survey data from SME tourism enterprises in Vietnam, the study tries to explain inter-firm behaviours based on integrating theories from different disciplines. The study reveals that cooperative intention is the main predictor of cooperative decision. Further, it confirms the positive influence of social impact and similarities between partners on inter-firm cooperation. The study provides theoretical and managerial foundations because the research addresses the relationships among these constructs in inter-firm context.
The Role of Theory in Explaining Motivation for Corporate Social Disclosures: Voluntary Disclosures vs ‘Solicited’ Disclosures

Corporate social disclosures (CSD) are primarily voluntary in nature and subsequently provide an area for research into motivational aspects of disclosures. The main focus of prior research has been whether corporate social disclosures constitute a discharge of accountability or are part of a process of legitimation. Prior research, however, ignores the emergence of an alternate style of corporate social disclosure, the 'solicited' disclosure. Increasingly companies are requested to report on their interactions with society in various forms. Non-government organisations (NGOs), regulatory agencies, ethical or socially responsible investment fund managers and other researchers are requesting social information from corporations. This shift from voluntary information provision to demanded information can be viewed as a natural consequence of the increasing pressures on corporations to be 'responsible', particularly in light of intensified world wide attention on unethical corporate behaviour and corporate collapse. These contemporary variants of social disclosure are worthy of scrutiny when considering these 'solicited' disclosures potentially reduce a corporation's power in defining the scope and nature of disclosures. Two theories, which are similar and derived from the broader political economy perspective, are commonly offered as explanations of motivations for social disclosures. Stakeholder theory offers an explanation of accountability to stakeholders. Legitimacy theory, on the other hand, suggests voluntary disclosures are part of a process of legitimation. This paper argues that these theoretical perspectives may provide greater insights into managerial motivation for disclosure if they are linked more explicitly to the nature of corporate social disclosure under examination: voluntary or solicited.
EXPERIMENTALLY REDUCING NEIGHBOR DENSITY AFFECTS REPRODUCTION AND BEHAVIOR OF A MIGRATORY SONGBIRD

Because populations of territorial birds are relatively stable compared to those of other animal taxa, they are often considered to be tightly regulated. However, the mechanisms that produce density-dependent feedbacks on demographic rates and thus regulate these populations are poorly understood, particularly for migratory species. We conducted a three-year density-reduction experiment to investigate the behavioral mechanisms that regulate the abundance of a Nearctic–Neotropical migrant passerine, the Black-throated Blue Warbler (Dendroica caerulescens), during the breeding season. We found that the number of young fledged per territory, territory size, and the proportion of time males spent foraging were significantly greater on territories around which neighbor density was experimentally reduced compared to control territories. Territory quality, proportion of nests depredated per territory, and male countersinging rates were not statistically different between treatments. These results indicate that i.
A Probabilistic Three-Phase Time Domain Electric Arc Furnace Model based on analytical method

An electric arc furnace (EAF) is known as nonlinear and time variant load that causes power quality (PQ) problems such as, current, voltage and current harmonics, voltage flicker, frequency changes in power system. One of the most important problems to study the EAF behavior is the choice of a suitable model for this load. Hence, in this paper, a probabilistic three-phase model is proposed based on recovered hidden Markov model (RHMM) in time domain. To recover the HMM , the coupling factor is proposed. This factor estimates the past observations and considers the effects of all observations in different states. Regarding to the intense fluctuations of various parameters of EAF, this factor can improve the EAF model in different operating stages. This subject causes that the proposed model is closed to the actual model. To train the RHMM, actual measured samples are used. Likewise, different parameters of EAF' power system as, flexible cables, electrode, busbar are exactly considering to achieve an accurate model. Comparing the results of experimental and proposed model indicates the accuracy of the proposed model.
Effects of Embedded Anomalies and Oral Reading Errors on Childen's Understanding of Stories1

The basic question asked by this study was, “Do mistakes made while reading interfere with comprehension? ” A secondary aim was to clarify the competing views of Gough (1972) who argues that the unskilled reader would not make hypotheses about what words in the text should be, and Goodman (1976a), who argues that the generation of tentative hypotheses about meaning is an inevitable part of the reading process. Three experiments were conducted. The first two were simulations in which skilled readers, about 9 years of age, read stories which varied according to embedded error type, difficulty, error rate, text access, and set strength. The third experiment was a naturalistic comparison study, using unskilled readers. Overall, the results offered support for both Gough and Goodman, depending on the kind of comprehension tested and the criterion for acceptability of responses. It seems that accuracy is necessary for atomistic precision; less so for global interpretation.
Performance Assessment and Prediction for Superheterodyne Receivers Based on Mahalanobis Distance and Time Sequence Analysis

The superheterodyne receiver is a typical device widely used in electronics and information systems. Thus effective performance assessment and prediction for superheterodyne receiver are necessary for its preventative maintenance. A scheme of performance assessment and prediction based on Mahalanobis distance and time sequence analysis is proposed in this paper. First, a state observer based on radial basis function (RBF) neural network is designed to monitor the superheterodyne receiver and generate the estimated output. The residual error can be calculated by the actual and estimated output. Second, time-domain features of the residual error are then extracted; after that, the Mahalanobis distance measurement is utilized to obtain the health confidence value which represents the performance assessment result of the most recent state. Furthermore, an Elman neural network based time sequence analysis approach is adopted to forecast the future performance of the superheterodyne receiver system. The results of simulation experiments demonstrate the robustness and effectiveness of the proposed performance assessment and prediction method.
Hydro-meteorological trends in the upper Indus River basin in Pakistan

We examined trends in several hydro-meteorological variables in the upper Indus River basin (UIRB) in Pakistan. To represent the diversity of hydro-meteorological conditions in the basin, mean monthly data from 20 meteorological and 8 hydrometric stations were analyzed for detection of trends using the non-parametric Mann-Kendall test in combination with the trend-free pre-whitening approach for correcting time series data sets for serial correlation. Sen's slope method, a non-parametric alternative for estimating a slope for a univariate time series, was used to determine the magnitude of trends. The meteorological variables we considered were: minimum temperature, maximum temperature, and precipitation, whereas the hydrological variable consid- ered was streamflow. For several of the variables, many more trends were identified than can be expected to occur by chance. Analysis of winter maximum temperature revealed an increasing trend with the trend in slopes of 1.79, 1.66, and 1.20°C per 39 yr for the upper, middle, and lower regions, respectively. Precipitation trends were inconsistent and showed no definite pattern. Trends in streamflow were found to be related to increasing trends in mean maximum temperature, partic- ularly in winter and spring seasons. Increased winter temperatures are likely to increase streamflow in winter and spring. During summer months streamflow will decrease and reduce the availability of water in the Tarbela Dam, thereby requiring changes in the reservoir operating policy towards more efficient management of available water.
Phage display-selected peptides for binding and synthesis of nanoparticles: ZnO as an example

Nanoparticles of metal oxides are widely used in bionanotechnology, particularly in bio-medical applications; e.g., construction of biosensors, separation of biological materials, molecular imaging, and anticancer and antimicrobial therapies. However, synthesis of these nanoparticles using physico-chemical methods is problematic, because such procedures require high-temperature processes and harsh chemical treatments. The use of peptides specifically binding particular nanoparticles or nanostructures and facilitating their synthesis appears to be an encouraging alternative. Specific peptides capable of such reactions may be identified with the use of the phage display method. In this mini-review, zinc oxide is discussed as an exemple material whose nanoparticles can be bound and synthesized by such peptides exposed on the surface of bacteriophage capsids. An analysis of reports on studies into methods of peptide-aided synthesis of ZnO nanoparticles has indicated that, despite the encouraging results obtained so far, further studies are necessary to optimize such procedures. This may also be true for nanoparticles of other materials, particularly metal oxides.
Electrochemical propertiesand thermal stability of cup-like shape gold nanostructures

Nanostructured surfaces are useful in enlargement of electroactive area of sensing electrodes. The electrodes are very sensitive with maintaining small electrode geometry. In this study, surfaces modified by cup-like gold nanoparticles were fabricated by electrochemical methods. Subsequently, electrochemical properties and thermal stability of fabricated nanostructured electrodes were studied. Thereafter, the electrochemical results were compared with unmodified flat gold layer and contribution of nanostructuring was evaluated. Stability of nanoparticles after thermal vacuum and air pressure treatment was studied using scanning electron microscope. These results are useful for subsequent research of nanostructured sensors.