Miracle-dz/UniFAR-FTUs huggingface dataset:
A quantitative analysis of Zimbabwe's land reform policy: An application of Zimbabwe SAM multipliers

Abstract This study was designed to quantitatively investigate the economy-wide impact of land reform policies in Zimbabwe. Land reforms came with the realm of independence in Zimbabwe. Four models were used to implement the reform policies. The paper uses the updated 1991 Social Accounting Matrix for Zimbabwe and the Central Statistics Office's household data on resettled families in Zimbabwe. The paper computes the sectoral SAM multipliers and then uses household data on resettled families to simulate the impact of specific land reform models on the economy. The simulated results show that land reform, if well planned and systematically and carefully implemented, could generate economy-wide benefits for Zimbabwe and could lead to income redistribution in favour of low-income household groups, while maintaining an increase in households' aggregate income.
Performance evaluation and comparison of single-phase and two-phase interleaving flyback micro-inverters for grid connected PV systems

Flyback converter based single-stage, micro-inverters are attractive solution for interfacing individual PV modules to the grid due to their low cost, high performance, ease of implementation, and galvanic isolation. In such applications, discontinuous conduction mode (DCM) of operation and interleaving techniques bring additional size and performance advantages such as eliminating reverse recovery loss, switching stress, EMI radiation, and improving efficiency. This paper focuses on performance evaluation of flyback micro-inverters achieving single-phase and interleaving operations with DCM operation. Design and implementation of 200 W single-phase and two-phase interleaved flyback micro-inverters are realized, detailed laboratory tests are conducted and benefits of interleaving technique are demonstrated.
Textual Affect Communication and Evocation Using Abstract Generative Visuals

In order to facilitate interaction in computer-mediated communication and enrich user experience in general, we introduce a novel textual emotion visualization approach, grounded in generative art and evocative visuals. The approach is centered on the idea that affective computer systems should be able to relate to, communicate, and evoke human emotions. It maps emotions identified in the text to evocative abstract animation. We examined two visualizations based on our approach and two common textual emotion visualization techniques, chat emoticons and avatars, along three dimensions: emotion communication, emotion evocation, and overall user enjoyment. Our study, organized as repeated measures within-subject experiment, demonstrated that in terms of emotion communication, our visualizations are comparable with emoticons and avatars. However, our main visualization based on abstract color, motion, and shape proved to be the best in evoking emotions. In addition, in terms of the overall user enjoyment, it gave results comparable with emoticons, but better than avatars.
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees

Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supervised learning addresses this problem by using unlabeled data together with labeled data to improve the performance. Co-Training is a popular semi-supervised learning algorithm that has the assumptions that each example is represented by two or more redundantly sufficient sets of features (views) and additionally these views are independent given the class. However, these assumptions are not satisfied in many real-world application domains. In this paper, a framework called Co-Training by Committee (CoBC) is proposed, in which an ensemble of diverse classifiers is used for semi-supervised learning that requires neither redundant and independent views nor different base learning algorithms. The framework is a general single-view semi-supervised learner that can be applied on any ensemble learner to build diverse committees. Experimental results of CoBC using Bagging, AdaBoost and the Random Subspace Method (RSM) as ensemble learners demonstrate that error diversity among classifiers leads to an effective Co-Training style algorithm that maintains the diversity of the underlying ensemble.
Efficient Algorithms for Real-Time GPU Volumetric Cloud Rendering with Enhanced Geometry

This paper presents several new techniques for volumetric cloud rendering using efficient algorithms and data structures based on ray-tracing methods for cumulus generation, achieving an optimum balance between realism and performance. These techniques target applications such as flight simulations, computer games, and educational software, even with conventional graphics hardware. The contours of clouds are defined by implicit mathematical expressions or triangulated structures inside which volumetric rendering is performed. Novel techniques are used to reproduce the asymmetrical nature of clouds and the effects of light-scattering, with low computing costs. The work includes a new method to create randomized fractal clouds using a recursive grammar. The graphical results are comparable to those produced by state-of-the-art, hyper-realistic algorithms. These methods provide real-time performance, and are superior to particle-based systems. These outcomes suggest that our methods offer a good balance between realism and performance, and are suitable for use in the standard graphics industry.
Can Investors’ Horizons Influence Firm-Specific Crash Risk?

We study the relation between the probability of future stock price crash and investors’ investment horizons. We focus on institutional investors because of their dominant market share in U.S. equities trading and their role in amplifying the financial crisis of 2008. Using skewness as proxy for firm-specific crash risk, we document a negative association between institutional ownership and skewness in equity returns. This inverse relation is however driven by short-term institutional investors, while the presence of long-term institutional investors has a positive effect on return skewness. Our results also show that crash risk is negatively related to short-term institutional investors’ trading behavior. In addition, we find that the presence of short-term institutional investors induces corporate risk-taking behavior. Our results are robust to alternative model specifications, endogeneity concerns, and alternative measures of crash risk and proxies of investors’ horizons. JEL classification: G12, G14
Foodborne and waterborne illness among Canadian Indigenous populations: A scoping review.

Background Indigenous populations are often at higher risk for foodborne illness than the general Canadian population. Objective To investigate the extent of the literature on the link between food safety and the occurrence of foodborne and waterborne illness in Canadian Indigenous populations. Methods A scoping review was conducted using search strings in five databases and grey literature to identify all papers that studied a Canadian Indigenous population and referred to any potential associations between food safety (including consumption and preparation of traditional foods and retail foods) or water safety practices and food or waterborne illness. Two authors screened papers based on inclusion and exclusion criteria. Included documents were analyzed for emergent themes. Results From 1,718 unique records identified, 21 documents were selected. Foodborne illness was most common in children up to 14 years old. Walrus, seal, caribou and whale were the most common traditional foods tied to foodborne illness and were primarily associated with botulism and trichinosis. Aside from consuming the food raw, fermentation was the most common traditional preparation method linked to foodborne illness. There was concern about the safety of retail food but no clear link was identified with foodborne illness. Lastly, although there was concern about tap water, the use of alternate water sources, such as untreated brook water, and hygiene and cleaning practices in communities with boil water advisories were the most common risk behaviours associated with waterborne illness. Conclusion Consumption of certain game meats, as well as the use of traditional fermentation practices may lead to an increased risk of foodborne illness among Indigenous populations. Concern about tap water may lead to use of unsafe alternate water sources. Further research is needed to examine potential culturally appropriate food and water safety opportunities.
Deacetylation of metabolic enzymes by Sirt2 modulates pyruvate homeostasis to extend insect lifespan

Diapause in insects is akin to dauer in Caenorhabditis elegans and hibernation in vertebrates. Diapause causes a profound extension of lifespan by low metabolic activity. However, the detailed regulatory mechanisms for low metabolic activity remain unknown. Here, we showed that low pyruvate levels are present in the brains of diapause-destined pupae of the cotton bollworm Helicoverpa armigera, and three enzymes pyruvate kinase (PK), phosphoenolpyruvate carboxykinase (PEPCK), and phosphoglycerate mutase (PGAM) are closely correlated with pyruvate homeostasis. Notably, Sirt2 can deacetylate the three enzymes to increase their activity in vitro. Thus, low Sirt2 expression in the brains of diapause individuals decreases PK and PEPCK protein levels as well as PGAM activity, resulting in low pyruvate levels and low tricarboxylic acid cycle activity and eventually inducing diapause initiation by low metabolic activity. These findings suggest that pyruvate is a checkpoint for development or lifespan extension, and Sirt2 is a negative regulator to extend lifespan in insects.
Isotropic differential phase contrast microscopy for quantitative phase bio‐imaging

Quantitative phase imaging (QPI) has been investigated to retrieve optical phase information of an object and applied to biological microscopy and related medical studies. In recent examples, differential phase contrast (DPC) microscopy can recover phase image of thin sample under multi‐axis intensity measurements in wide‐field scheme. Unlike conventional DPC, based on theoretical approach under partially coherent condition, we propose a new method to achieve isotropic differential phase contrast (iDPC) with high accuracy and stability for phase recovery in simple and high‐speed fashion. The iDPC is simply implemented with a partially coherent microscopy and a programmable thin‐film transistor (TFT) shield to digitally modulate structured illumination patterns for QPI. In this article, simulation results show consistency of our theoretical approach for iDPC under partial coherence. In addition, we further demonstrate experiments of quantitative phase images of a standard micro‐lens array, as well as label‐free live human cell samples.
The Impact of External Environmental Conditions on Corporate Capital Structure: Evidence from Hotels and Travels Sector in Sri Lanka

In the modern financial era, companies adjust their capital structure to cope with the external and internal environmental conditions. The purpose of this study is to investigate the influence of external environment or in other words, institutional and macroeconomic conditions on capital structure decisions of firms listed under hotels and travels sector. The sample of the study comprised with 26 listed companies in hotels and travels sector of Colombo Stock Exchange over a period of 10 years from 2004 to 2013. The analysis is carried out by employing panel data econometric techniques. The empirical results demonstrate in overall institutional and macroeconomic conditions have significant influences on the capital structure decisions of firms listed in the hotels and travel sector. The findings of the study which is a featured departure from the previous studies on capital structure which emphasize the role that prevailing institutional and macroeconomic conditions play in determining the capital structure decisions in the listed firms in Sri Lanka.
Employment Adjustment and Part-Time Jobs: The U.S. and the U.K. In the Great Recession

We document that fluctuations in part-time employment play a major role in movements in hours per worker, especially during cyclical swings in the labor market. Building on this result, we propose a novel representation of the intensive margin based on a stock-flow framework. The evolution of part-time employment is predominantly explained by cyclical changes in transitions between full-time and part-time employment, which occur overwhelmingly at the same employer and entail large changes in individuals' working hours. We discuss implications for a large class of macroeconomic models that map individual decisions along the extensive/intensive margins onto aggregate labor market outcomes.
Text-independent Speaker Verification Using Convolutional Deep Belief Network and Gaussian Mixture Model

There has been much interest in new deep learning approaches for representing and extracting high-level features for audio processing. In this paper convolutional deep belief network was used to generate new speech features for textindependent speaker verification. Structure and parameters of a convolutional deep belief network were described. New high-level speech features were extracted using proposed method. Relevance of speaker verification systems for mobile authentication was considered. Gaussian mixture model and universal background model speaker verification system used for experiments was described. Speaker verification accuracy using extracted features was evaluated on a 50 speaker set and a result is presented. Different layers and combinations of layers of convolutional deep belief network were used as a features for a text-independent speaker verification. High level features extracted by convolutional deep belief network were illustrated and analyzed. Reasons of insufficient verification accuracy were described. High-level features extracted by the third layer could be used for gender recognition. Keywords—speaker verification; speech features; gmm-ubm system; speech processing; cdbn; feature extraction; deep learning; neural networks
Magmatic and tectonic extension at mid‐ocean ridges: 2. Origin of axial morphology

We investigate the origin of mid‐ocean ridge morphology with numerical models that successfully predict axial topographic highs, axial valleys, and the transition between the two. The models are time‐dependent, simulating alternating tectonic and magmatic periods where far‐field extension is accommodated by faulting and by magmatism, respectively. During tectonic phases, models predict faults to grow on either side of the ridge axis and axial height to decrease. During magmatic phases, models simulate magmatic extension by allowing the axial lithosphere to open freely in response to extension. Results show that fault size and spacing decreases with increasing time fraction spent in the magmatic phase FM. Magmatic phases also simulate the growth of topography in response to local buoyancy forces. The fundamental variable that controls the transition between axial highs and valleys is the “rise‐sink ratio,” (FM/FT)(τT/τM), where FM/FT is the ratio of the time spent in the magmatic and tectonic periods and τT/τM is the ratio of the characteristic rates for growing topography during magmatic phases (1/τM) and for reducing topography during tectonic phases (1/τT). Models predict the tallest axial highs when (FM/FT)(τT/τM) ≫ 1, faulted topography without a high or valley when (FM/FT)(τT/τM) ∼ 1, and the deepest median valleys when (FM/FT)(τM/τT) < 1. New scaling laws explain a global negative correlation between axial topography and lithosphere thickness as measured by the depths of axial magma lenses and microearthquakes. Exceptions to this trend reveal the importance of other behaviors such as a predicted inverse relation between axial topography and spreading rate as evident along the Lau Spreading Center. Still other factors related to the frequency and spatial pervasiveness of magmatic intrusions and eruptions, as evident at the Mid‐Atlantic and Juan de Fuca ridges, influence the rise‐sink‐ratio (FM/FT)(τT/τM) and thus axial morphology.
Detection of Listeria monocytogenes in Ready-to-Eat Meat Products

Problem statement: The objective of this study was to develop a rapid and sensitive method for the detection of Listeria monocytogenes and to screen large number of ready-to-eat (RTE) meat samples. Approach: A total of 250 fresh RTE meat samples of different varieties (chicken, turkey, beef, pork and cold cuts) were purchased from local grocery stores. Results: From the 250 total samples, 50 samples were randomly selected and subjected to DNA extraction, and immunomagnetic Separation (IMS) followed by RT-PCR analysis using primers against L. monocytogenes specific gene (hlyA). Five RTE samples negative by culture and by RT-PCR were spiked with L. monocytogenes (ATCC-19111) and used as positive controls. While all positive samples were detected as positive, all 50 samples were negative with both methods i.e., IMS followed by hlyA gene-based RT-PCR assay and the standard culture methods. Following this, all the 250 samples were tested by standard culture method as well as the IMS+RT-PCR assay. Five samples (2.0%) were presumptively diagnosed as positive for Listeria on Oxford agar. All the five confirmed to be positive for L. monocytogenes by IMS+RT-PCR assay. Conclusion/Recommendations: The IMS + RT-PCR procedure was considerably more rapid and required only 28 h compared to 96-120 h for the conventional culture method. This method would be useful as the criteria for addressing the costly meat recalls and reducing outbreaks.
Long Chain n-3 Fatty Acids Improve Depression Syndrome in Type 2 Diabetes Mellitus

Background: Type 2 diabetes mellitus (T2DM) is commonly associated with depressive symptoms, which affect prognosis and quality of life. We investigated the antidepressant effects of n-3 fatty acids (n-3FAs) monotherapy (without conventional antidepressants) for T2DM patients with mild to moderate depressive symptoms. Methods: A 10-wk, placebo-controlled, double-blind, parallel-group (1:1 ratio) randomized trial of n-3FAs (2700 mg/day EPA: DHA ratio=2) versus placebo in 88 Iranian diabetic patients with mild to moderate depression based on Beck Depression Inventory II (BDI-II-PERSIAN) was conducted. This study started from July 2014 to January 2015 in Tehran University of Medical Sciences, Tehran, Iran. The primary event was defined as worsened, non-changed, or inconsiderably improved depression (<5 unit decrease in BDI-II-PERSIAN depression scores after treatment) (ClinicalTrials.gov Identifier: NCT02261545). Results: Randomly, 44 T2DM patients were treated with n-3FAs supplements and 44 cases received placebo (three patients discontinued). n-3FAs could significantly protect patients against the aforesaid event and exhibit satisfactory prevention (number needed to treat with 95% confidence interval: 2.52, 1.71–4.74). No serious adverse reactions were reported. Conclusion: n-3FAs supplementation had significant antidepressant effects in T2DM patients with mild to moderate depressive symptoms, not confounded by metabolic factors and disease duration.
Tear film assessments for the diagnosis of dry eye

Purpose of reviewDry eye disease (DED) is a complex, multifactorial condition that is challenging to diagnose and monitor clinically. To date, diagnosis has consisted largely of self-reported symptom questionnaires and a collection of clinical tests including vital dye staining, estimation of tear breakup time and Schirmer's testing, as no gold standard exists. As the dry eye field has made progress in understanding disease pathogenesis, new methods for assessment of this condition have been developed. Recent findingsDED is now known to be characterized by tear hyperosmolarity and ocular surface inflammation, and there are now commercially available devices that accurately and reliably measure tear osmolarity and matrix metalloproteinase 9, a marker of inflammation and tissue breakdown. In addition, there are a variety of imaging modalities that have shown promise in their ability to identify patients with DED by assessing tear film dimensions and tear film instability. SummaryThere is a significant need for the development of tear film assessments for accurate diagnosis and monitoring of dry eye. There are a number of new devices and techniques that have shown promise in their ability help clinicians manage patients with DED.
Active stereoscopic camera to build an occupancy grid for autonomous navigation

Using a SLAM technique, known as Rao-Blackwellized particle filter (RBPF), this work proposes to compare the performance of this solution in two situations: (a) using a rangefinder laser sensor to build an occupancy grid, as done in previous works in literature, and (b) using an active stereoscopic camera. This will allow to generate an occupancy grid, simultaneously while doing the robot's localization, using only one device, reducing the payload and costs for this task. A future work will be performed to resolve the problems observed in this work.
One solution of STB users cloud based profiling

The purpose of this paper is to present a solution for adaptable and efficient user profiling system for set-top-box (STB) devices. The system is set in the cloud environment and based on TR-069 remote management protocol and TR-135 data model for STB devices. The proposed solution allows the development of better and more precise applications for recommending TV and Internet based multimedia content. The system that we propose enables further creation of services that provide better, smarter and more comfortable experience for STB users.
Contextualized Usage-Based Material Selection

In this paper, we combine several NLP-functionalities to organize examples drawn from corpora. The application’s primary target audience are language learners. Currently, authentic linguistic examples for a given keyword search are often organized alphabetically according to context. From this, it is not always clear which contextual regularities actually exist on a syntactic, collocational and semantic level. Showing information at different levels of abstraction will help with the discovery of linguistic regularities and thus improve linguistic understanding. Practically this translates in a system that groups retrieved results on syntactic grounds, after which the examples are further organized at the hand of semantic similarity within certain phrasal slots. Visualization algorithms are then used to show focused information in phrasal slots, laying bare semantic restrictions within the construction.
Chemical substance classification using long short-term memory recurrent neural network

This paper proposed a chemical substance detection method using the Long Short-Term Memory of Recurrent Neural Networks (LSTM-RNN). The chemical substance data was collected using a mass spectrometer which is a time-series data. The classification accuracy using the LSTM-RNN classifier is 96.84%, which is higher than 75.07% of the ordinary feed forward neural networks. The experimental results show that the LSTM-RNN can learn the properties of the chemical substance dataset and achieve a high detection accuracy.