Miracle-dz/UniFAR-FTUs huggingface dataset:
A DEMONSTRATION OF THE APPLICATION OF THE C . PERFRINGENS RISK ASSESSMENT FOR ESTIMATION OF RISK MANAGEMENT METRICS

Introduction The U.S. Department of Agriculture’s (USDA’s) Food Safety and Inspection Service (FSIS) is exploring quantitative risk assessment methodologies to incorporate the use of Codex Alimentarius’ newly adopted risk management metrics, e.g., Food Safety Objective (FSO), Performance Objective (PO) and Microbiological Criterion (MC). It is suggested that use of these metrics would tie more closely to the results of quantitative microbial risk assessments (QMRAs) to public health outcomes and a country’s Appropriate Level of Protection (ALOP). For the purpose of this demonstration, the ALOP is set as the number of human illnesses caused by the hazard within ready-to-eat (RTE) and partially cooked meat and poultry products. The FSO is the maximum frequency and/or concentration of the hazard in a food at the time of consumption and is preceded by the PO, which is the maximum frequency and/or concentration of a hazard in a food at a specified step in the food chain before the time of consumption. Finally, the MC defines the acceptability of a product or a food lot as determined by a sampling plan that is based on absence/presence, or concentration testing of the hazard.
Australasian Conference on Information Systems 2018 , Sydney , Australia eLearning performance 1 Assessing the impact of using instant messaging in eLearning on the performance of teaching and learning in higher education

There are growing interests in improving teaching and learning performance through eLearning using specific emerging technologies in higher education. As a result, understanding the impact of using such technologies on the performance of teaching and learning is becoming important. This experimental study investigates the impact of eLearning using instant messaging on the performance of teaching and learning in higher education in developing countries. Pre-test and post-test surveys are used for collecting experimental data from participants to investigate the impact of using instant messaging on teaching and learning. Data analysis conducted quantitatively using SPSS reveals that eLearning using instant messaging improves teaching and learning. In particular, the use of instant messaging in eLearning is more effective than face-to-face teaching and learning with respect to the overall performance in the classroom. This leads to the conclusion that eLearning using instant messaging could transform teaching and learning in higher education in developing countries.
Retaining Expression on De-identified Faces

The extensive use of video surveillance along with advances in face recognition has ignited concerns about the privacy of the people identifiable in the recorded documents. A face de-identification algorithm, named kk-Same, has been proposed by prior research and guarantees to thwart face recognition software. However, like many previous attempts in face de-identification, kk-Same fails to preserve the utility such as gender and expression of the original data. To overcome this, a new algorithm is proposed here to preserve data utility as well as protect privacy. In terms of utility preservation, this new algorithm is capable of preserving not only the category of the facial expression (e.g., happy or sad) but also the intensity of the expression. This new algorithm for face de-identification possesses a great potential especially with real-world images and videos as each facial expression in real life is a continuous motion consisting of images of the same expression with various degrees of intensity.
Cytotoxic And Genotoxic Properties Of Saraisa (Muntingia Calabura) Bark Extract

This study examined the cytotoxic and genotoxic properties of saraisa (Muntinga calabura). This quantitative-experimental study used the Brine Shrimp Lethality (BSLA) and Allium cepa root growth inhibition assays to test its cytotoxic and genotoxic properties, respectively. These properties were evaluated based from the mortality rate of the brine shrimp nauplii and the root length inhibition of onion (A. cepa) after being exposed to varying extract concentrations. In this experiment, the properties were assessed by comparing the cytotoxic and genotoxic properties of the different concentrations with the negative control using F-test and LSD pairwise comparison. The test for cytotoxicity revealed that M. calabura demonstrated a moderate level of cytotoxicity against brine shrimp nauplii, with a lethal concentration (LC50) of 143.598 parts per million (ppm). There was a significant difference between the cytotoxic property of the different concentrations of the extract and the negative control. Furthermore, the root growth inhibition test revealed the high genotoxic effect of the extract by successfully inhibiting the growth of A. cepa roots. The bioactivity of M. calabura reported in this study is an indication of the presence of potent compounds which are good sources of important drug candidates. Thus, the study found the need to investigate further M.calabura‟s biological properties for its possibility to be a potential drug candidate.
Pathological Effects of Crud Trichothecenes on Swiss Mice

Trichothecenes are natural secondary metabolites causing economic losses and health hazard to human and farm animals which are produced by several species of Fusarium and some other genera on different agricultural commodities. Study on trichothecenes mycotoxicosis revealed morphological, biochemical, and histopathological changes. After intraperitoneal injection of the toxin in male mice with different concentration for 35 days shows marked increase in body weight, dyspanea, shivering, bristling up of hair, hair falling, anomalies of eyes, and irritation around neck, also abdominal hemorrhage and clot accumulation in abdomen. In addition to inclusion (retention) cyst forms on liver. The biochemical studies on liver function by measuring GPT and GOT enzymes level have been done. An increase level of these enzymes in treated animal in comparison with control animal which indicating abnormal function of liver observed. The histopathological study on sections from the liver of treated animal with trichothecenes revealed many alterations in liver which includes congestion, kupffer cells hyperplasia, dilated sinusoids and mononuclear cells infiltration around the portal area.
Australasian Conference on Information Systems Limpin & Sison 2018 , Sydney , Australia Driver ’ s Tactics in Ridesharing 1 Drivers ’ Tactics in Ridesharing Economy in the Philippines

Increasing mobility needs, coupled with the lack of adequate public transportation has led to the popularity of ridesharing services in the Philippines, which in 2015 became the first country to implement a regulatory framework for ridesharing through transportation network company (TNC) apps. This study aims to explore the participation of drivers in the ridesharing economy in Metro Manila. Employing thematic analysis, the driver tactics are viewed as falling under one of six categories: surge chasing, request skipping, dual driving, colorum, operator tactics and focusing. While many of the themes confirm the findings of earlier studies, some ridesharing tactics found in the Philippine context provide nuances that may offer insights on the drivers’ use of ridesharing platforms. Specifically, these strategies suggest that users find new ways to use the technology to support their motivations, resulting in a notion deviant to the original purpose of ridesharing.
Using Semantic Role Labeling to Combat Adversarial SNLI

Natural language inference is a fundamental task in natural language understanding. Because of the understanding required to assess the relationship between two sentences, it can provide rich, generalized semantic representations. In this study, we implement a sentenceencoding model using recurrent neural networks. Our hypothesis was that semantic role labels, along with GloVe word embeddings, would give the sentences rich representations, making the model not only more successful on the original SNLI challenge, but also more robust to adversarial examples. However, our findings show that adding the SRL information does not improve the performance of our baseline model on either the SNLI task or the adversarial data sets. 1 Problem and Related Work Natural language inference (NLI) is the problem of determining whether a hypothesis sentence H follows from a premise sentence P. NLI is a fundamental task in natural language understanding because of the understanding required to assess the relationship between two sentences. It has applications in many tasks, including question answering, semantic search, and automatic text summarizing. It is an ideal testing ground for theories of semantic representation, and the training for NLI tasks can provide rich, generalized semantic representations. NLI has been addressed using a variety of techniques, including symbolic logic, knowledge bases, and, in recent years, neural networks (Bowman et al., 2015). The landscape of NLI models is shown in Figure 1. (Bowman et al., 2015) proposes a straightforward architecture of deep neural networks for NLI. In their architecture, the premise and the hypothesis are each represented by a sentence embedding vector. The two vectors are fed into a multi-layer neural network to train a classifier. It achieved an accuracy of 77.6% using LSTM networks on the SNLI corpus. (Rocktschel et al., 2016) improves the aforementioned LSTM model by applying a neural attention model. The basic architecture is the same as (Bowman et al., 2015), which is based on sentence embeddings for the premise and the hypothesis. The key difference, which (Rocktschel et al., 2016) uses to improve performance, is that the embedding of the premise takes into consideration the alignment between the premise and the hypothesis. This attention-weighted representation of the premise improves the model performance to an ac-
Productive performance of Bovans brown and Hy-sex brown laying hens as affected by body weight at 20 weeks of age

Two hundred and fifty two from Bovans brown (BV) and Hy-sex brown (HS) pullets at 20 weeks of age were used in this experiment. Each strain included one hundred and twenty six of hens were classified according to body weight (X); into three category groups (42 hens of each) being heavy body weight averaged (1440 and 1740 g), medium body weight (standard body weight, 1323 and 1647 g) and light body weight (1236 and 1547 g) in Bovans brown and Hy-sex brown pullets, respectively. The hens of each group divided into six replicates (7 birds each). Each replicate was kept in wire cage (7 hens per cage) for 68 weeks of age. The obtained results could be summarized as follows: The medium birds of Bovans Brown strain (MBV) showed significantly (P≤0.05) higher hen day egg production (HDP) by 4.0 and 5.4%, hen housed egg production (HHP) by 4.0 and 12.3%, eggs number (EN) by13.4 and 18.4 eggs and egg mass by 0.90 and 1.38 kg/hen and exceeded economical efficiency by 17.5 and 16.2% as compared with those of heavy and light birds of Bovans brown (HBV and LBV), respectively. The HBV showed a significantly (P≤0.05) higher egg weight (EW) by about 1.8 and 2.4% and feed consumption by 2.5 and 4.4% as compared with that of MBV and LMV, respectively. The heavy and medium birds of Hy-sex brown strain (HHS and MHS, respectively) showed significantly (P≤0.05) higher HDP by 5.0 and 5.2%, HHP by 8.6 and 8.8%, EN by 16.9 and 17.6 eggs, EW by 1.8 and 1.5%, EM by 1.26 and 1.16 Kg/hen, FC by 2.1 and 1.1% and EE by 14.9 and 18.3%, respectively as compared with that of light birds of Hy-sex brown (LHS). There were no significant differences in cumulative feed conversion (g feed/ g egg mass or g feed/ 12 eggs) among three body weight categories of both BV and HS strains. No deaths occurred of high and medium birds of both BV and HS strains at all ages, while the mortality rate was 8.0 and 4.8% for LBV and LHS, respectively. El-Sagheer and Hassanein, 2006. Egyptian Poultry Science Journal, Vol. 26, (II): 731-747. 732 It could be concluded that, the medium birds (standard body weight) of BV and medium and heavy birds of HS recorded the best EE value as compared with the other body weight categories. (
CUTKB at NTCIR-14 QALab-PoliInfo Task

The news has spread quickly due to the development of social media. It will be a problem when the fake news has gone viral. Since the fake news was related to the politics in many cases, we focused on automatic estimation of fact-checkability using Japanese Regional Assembly Minutes Corpus. To verify the fact-checkability in the sentences correctly, it is essential to focus on the sentences which contain the evidence of the facts. In this paper, we explain our deep learning model to estimate “Relevance”, “Fact-checking”, and “Stance” for the sentences of the Minutes. Furthermore, we investigate whether the model combining CNN and LSTM is effective to check the facts.
Efficient motion analysis of IT support for information retrieval at manual workplaces

In today’s business environment, the trend towards more product variety and customization is unbroken. Due to this development, the need of agile and reconfigurable production systems emerged to cope with various products and product families. To design and optimize production systems as well as to choose the optimal product matches, product analysis methods are needed. Indeed, most of the known methods aim to analyze a product or one product family on the physical level. Different product families, however, may differ largely in terms of the number and nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production system. A new methodology is proposed to analyze existing products in view of their functional and physical architecture. The aim is to cluster these products in new assembly oriented product families for the optimization of existing assembly lines and the creation of future reconfigurable assembly systems. Based on Datum Flow Chain, the physical structure of the products is analyzed. Functional subassemblies are identified, and a functional analysis is performed. Moreover, a hybrid functional and physical architecture graph (HyFPAG) is the output which depicts the similarity between product families by providing design support to both, production system planners and product designers. An illustrative example of a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of thyssenkrupp Presta France is then carried out to give a first industrial evaluation of the proposed approach. © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 28th CIRP Design Conference 2018.
Twitter as an Alternative Review Site

Online reviews are an important source of consumer opinions. They provide large quantities of data on consumer preferences and opinions. Twitter is a widely used microblogging social media platform, with 126 million daily users and 500 million tweets posted per day. Tweets posted to the site can often take the form of a review. This project will focus on harnessing these reviews and using them to help generate recommendations in the CoRE recommender system.
Concern-Alignment in Joint Inquiry for Consensus-Building

‘Concern Alignment in Conversations’ project aims to establish a theoretical and descriptive framework to capture both discourse structures and underlying rational and affective processes in human-human joint consensus-building interactions through empirical examinations of reallife conversations. Concern alignment model has been developed to address the problem of elucidating high-level dialogue structures manifested in human-human negotiations for consensusbuilding. The central idea is to conceptualize a dialogue interaction as an exchange of concerns and proposals.
The effects of methyl jasmonate and salinity on germination and seedling growth in Ocimum basilicum

About 10 percen of lands around the world under crops planting are affected by salinity. Therefore, comprehensive researches have been conducted to minimize the harmful effects of salinity in agriculture. The purpose of this study is examination of the Mmethyl jasmonate effect on reducing the effects of salinity in germination and vegetative stages of the basil plant.For the methyl jasmonate treatment, seeds were soaked in methyl jasmonate (0,0/1 and 0/01 μM) and then seeds were placed on filter papers wet using NaCl (50, 100, 200 mM). Then, the morphological parameters examined. The results indicated that high concentration of salinity cause to decrease in germination percentage and Methyl jasmonate cause increase in germination percentage, and this indicated the positive effect of methyl jasmonate on improvement of stress conditions in plant. Furthermore, salinity increases the growth of root and shoot, and methyl jasmonate offsets this reduction.
Comparative study of thermal inactivation kinetics of Salmonella spp . in peanut butter and peanut butter spread q

Peanut butter has been implicated in multi-state outbreaks of salmonellosis in recent years. Studies have shown that Salmonella exhibited increased thermal resistance in peanut butter. However, little is known about the effect of product formulation on the kinetics of survival of Salmonella during thermal treatment. Therefore, the objective of this research was to compare the thermal resistance of Salmonella in four commercially available peanut butter and spread products, and evaluate the effect of product formulation on the survival of this pathogen during heating. Four peanut butter and spread samples, including Omega 3 (A), regular fat (B), reduced sugar (C), and reduced fat (D), inoculated with a 6-strain cocktail of Salmonella spp. , were heated at 70, 75, 80, 85, and 90 C. Experimental results showed that the highest thermal resistance of Salmonella was found in the samples with reduced fat, while the least in the samples with Omega 3 formulation. No significant difference in the bacterial thermal resistance was observed in the regular fat and reduced sugar formulations. The Weibull survival model was used to describe the survival curves. Results showed that the average exponent (shape factor) of the model ranged from 0.38 to 0.662, suggesting progressively decreased rate of inactivation during heating. The scale (rate) coefficients of the model increased linearly with temperature. The calculated minimum lethal temperature for Salmonella was 54.8, 59.8, 59.5, and 63.9 C in samples A, B, C, and D, respectively. No tail effect was observed. The results of this study suggest that proper formulation of peanut butter and spread may enhance thermal inactivation of Salmonella. Published by Elsevier Ltd.
Long-term Autonomous Mobile Manipulation under Uncertainty Extended Abstract

We describe a hierarchical belief space planning framework to achieve robust long-term autonomous mobile manipulation behavior under uncertainty. The approach relies on condensing belief distributions across different abstractions to simultaneously suppress uncertainty and mitigate risk at run-time. We evaluate this system in an experimental domain that requires a robot to monitor and clean a dynamic unstructured environment, executing hundreds of physical actions without failures that require human intervention. Results indicate that this framework provides a sound basis for cognitive robots in uncertain and dynamic environments.
An Agent-Oriented Programming Language with Intention Driver

An agent-oriented programming language with intention driver is proposed, which is called AOPLID. Based on open situation calculus, AOPLID can be regarded as an improvement of GOLOG that is based on situation calculus. AOPLID can formalize some elements of the agents mental state, namely belief, intention, capability and strategy. A belief revision operator is introduced in AOPLID to deal with the communication and exogenous events. AOPLID solves the problems GOLOG faces, such as inconvenience of describing the agent抯 mental state, lack of communication. The syntax of the AOPLID and its semantic under the OSC are presented. An example program of AOPLID that describes the coffee machine is given too.
Fragility of layout-based and visual GUI test scripts: an assessment study on a hybrid mobile application

Context: Albeit different approaches exist for automated GUI testing of hybrid mobile applications, the practice appears to be not so commonly adopted by developers. A possible reason for such a low diffusion can be the fragility of the techniques, i.e. the frequent need for maintaining test cases when the GUI of the app is changed. Goal: In this paper, we perform an assessment of the maintenance needed by test cases for a hybrid mobile app, and the related fragility causes. Methods: We evaluated a small test suite with a Layout-based testing tool (Appium) and a Visual one (EyeAutomate) and observed the changes needed by tests during the co-evolution with the GUI of the app. Results: We found that 20% Layout-based test methods and 30% Visual test methods had to be modified at least once, and that each release induced fragilities in 3-4% of the test methods. Conclusion: Fragility of GUI tests can induce relevant maintenance efforts in test suites of large applications. Several principal causes for fragilities have been identified for the tested hybrid application, and guidelines for developers are deduced from them.
Semantic markup in discussion fora

Discussion tools in existing LEs have few or no integrated tools to analyse student learning. This paper proposes tools not only for integrating social network analytics, but also why we need to semantically tag and track key concepts within posts in order to make student learning in discussions visible. This paper will argue for the importance of semantic markup in discussion tools using screenshots of existing LEs and UI mockups of semantically aware discussion tools to argue the case for this element of next generation LEs
Multiple Kernel Learning via Multi-Epochs SVRG

This work proposes a multiple kernel learning (MKL) descent strategy based on multiple epochs of stochastic variance reduced gradients (i.e. multi-epochs SVRG). The proposed descent strategy takes place with a constant-size learning step, that is entangled to the evolution of the kernels combination coefficients, and hence corrected in between epochs. This descending regime leads to an improved MKL bound that exhibits a linear dependency on the number of samples n, and sublinear in both the number of kernels F and tolerance error ε. In particular, for an `p-norm MKL, the proposed method is able to find an ε-accurate solution in a complexity O(F 1/q · n log( 1ε )), where q is the dual norm. This matches the optimal convergence rate reported for (non-accelerated) strongly-convex objectives and improves over other state-of-the-art MKL solutions.