Miracle-dz/UniFAR-FTUs huggingface dataset:
MODELLING THE MALAYSIAN HERITAGE FOOD LOYALTY INTENTION: THE EFFECTS OF SUBJECTIVE KNOWLEDGE, ATTITUDE, AND SATISFACTION OF INTERNATIONAL TOURISTS’ FOOD CULTURAL EXPERIENCE

Cultural heritage food experience holds a boundless impression on tourists’ loyalty towards a tourism destination. To attract more international tourists to Malaysia, the role of Malaysian Heritage Food as the most valuable asset need to be expanded by safeguarding the uniqueness of the food culture from fading. Hence, this study aims to investigate international tourists’ perspectives on Malaysian Heritage Food (MHF), delineate the dimensions of Subjective Knowledge, Perceived Importance of Malaysian Food Culture, and Food Culture Involvement and to scrutinize the significant effect of predictors on Loyalty Intention. Finally, to examine the mediating effect of Tourist Satisfaction on the association of Tourist Attitude and Loyalty Intention, quantitative survey was conducted via self-administered questionnaire. The Structural Equation Modeling was performed to examine the hypotheses which backbone by the Expanded Rational Expectations Intention model. Findings demonstrated that international tourists had consumed MHF. All the tested variables have significant effect on Loyalty Intention. Finally, this study assists to endure the unique Malaysian food culture and to strengthen Malaysia as a food tourism destination in the world.
Bioactive Compounds of Flaxseed as Natural Antioxidants and Anticancer

The objective of this study was to investigate the content of biologically active compounds and antioxidant activity (AOA) of full fat flaxseed flour (FFF), roasted full fat flaxseed flour (RFFF), defatted flaxseed flour (DFF) and roasted defatted flaxseed flour (RDFF) flour as well as to evaluate anticancer effect of lignans ethanolic extracts from defatted and roasted defatted flaxseed for in vitro cytotoxicity against breast and colon carcinoma cell lines. The results revealed that roasted defatted flaxseed flour samples (RDFF) contained higher values of crude protein (32.86%), ash (6.60%), crude fiber (14.03%) and total carbohydrate (42.16%) than other flaxseed flour samples. Results showed that RDFF had significantly (P<0.05) the highest amounts of total phenolic contents, total flavonoid contents, tannins content and antioxidant activity (871.15 mg GAE/100g, 199.12 mg CE/100g, 83.51 mg CE/100g and 78.99%, respectively). Meanwhile, FFF contained the lowest values (643.04 mg GAE/100g, 112.46 mg CE/100g, 60.33 mg CE/100g and 75.80%, respectively). It was observed that, ferulic acid was the predominant phenolic acid in defatted flaxseed samples. Also, Secoisolariciresinol diglucoside (SDG) is the predominant lignans precursor present in flaxseed. Furthermore, DFF and RDFF were higher in lignans values compared to that of full fat and roasted full fat flaxseed flours. Cytotoxicity effect of lignans ethanolic extracts from defatted and roasted defatted flaxseed on colon carcinoma cell line (HCT) and breast carcinoma cell line (MCF-7) increased as the extract concentration increased. RDFF had strong anticancer activity toward two tested cell lines (MCF-7 and HCT) with the half maximal inhibitory concentration (IC50) values (29.0 and 31.4 μg/ml, respectively). While, defatted flaxseed revealed anticancer activity against (HCT) cell line (with value 48.2 μg/ml of IC50) compared to (MCF-7) cell line at concentration under investigation (12.5, 25, 50 and 100 μg/ml of lignans extract).
Feature identification using acoustic signature of Ocean Researcher III of Taiwan

Underwater acoustic signature identification has been employed as a technique for detecting underwater vehicles, such as in anti-submarine warfare or harbour security systems. The underwater sound channel, however, has interference due to spatial variations in topography or sea state conditions and temporal variations in water column properties, which cause multipath and scattering in acoustic propagation. Thus, acoustic data quality control can be very challenging. One of challenges for an identification system is how to recognise the same target signature from measurements under different temporal and spatial settings. This paper deals with the above challenges by establishing an identification system composed of feature extraction, classification algorithms, and feature selection with two approaches to recognise the target signature of underwater radiated noise from a research vessel, Ocean Researcher doi:10.21914/anziamj.v59i0. 12655, c © Austral. Mathematical Soc. 2019. Published July 25, 2019, as part of the Proceedings of the 13th Biennial Engineering Mathematics and Applications Conference. issn 1445-8810. (Print two pages per sheet of paper.) Copies of this article must not be made otherwise available on the internet; instead link directly to the doi for this article.
Reduction of crude protein in diets fed to lactating Holstein-Gyr cows

Abstract: The objective of this work was to evaluate the effect of reducing crude protein (CP) contents in diets with a constant metabolizable protein content on the intake, performance, nitrogen balance, and nutrient digestibility of lactating Holstein-Gyr cows. Animals (n = 24, 103±23 days in milk) were allocated to four treatments (n = 6 per group) with different CP contents: 127, 132, 139, and 156 g kg-1 dry matter (DM). DM intake was not affected by treatments. CP intake and digestibility increased linearly with higher CP contents. Milk yield (23.7±3 kg per day) and the percentages of milk protein (3.3±0.2%) and fat (3.8±0.5%) were not affected by CP reduction. Milk and blood urea nitrogen increased linearly with the increase of CP in the diet, similarly to urinary nitrogen excretion. Nitrogen use efficiency was 29.8 and 22.4% when CP was 127 and 156 g kg-1 DM, respectively. Reducing CP in diets fed to mid-lactating Holstein-Gyr cows increases nitrogen use efficiency and maintains the productive performance of the cows.
Transferable Odor Differentiation Models for Infectious Disease Diagnostics

markdownabstract__Abstract__ In recent years the interest for the application of an electronic nose (eNose) in medical Diagnostics is increasing. There is a need for this since eNose Diagnostics is non-invasive, easy to run, fast and cheap. The eNoses, now on the market, however, turn out to be unsuitable for large-scale application. This is mainly due to insufficient reproducibility of measurement results. In this work an eNose is used which is cheap and suited for mass applications. The usage of advanced temperature control guarantees the reproducibility between eNoses. In practice, this means that a once developed analysis model for a specific disease easily can be transferred to any number of other eNoses. Application of mass-produced components keeps the cost low. In the research it is shown that temperature variation is the main cause of the significant differences in measurement characteristic between the metal oxide sensors on which the eNose is based. To illustrate the practical applicability pilot studies are described for sepsis (bacterial infection of the blood), tuberculosis (TB) and metritis (infection of the uterus in cows). In the sepsis and metritis studies the measurements were conducted in the headspace of the blood cultures and uterus mucus respectively. In the tuberculosis study the exhaled breath of patients analyzed. For the sepsis diagnostics 30 eNoses are used to identify 11 to identify clinical relevant pathogens in blood. The eNose can significantly speed up the diagnostic process: on average 78% of the pathogens were correctly identified within 6-8 hours after inoculation in contrast to the 24 hours typically needed with the current methods. The TB-study was conducted in Dhaka (Bangladesh) with 3 eNoses. It turned out to be possible to distinguish between healthy people and those with active TB infection [sensitivity 93.5%, specificity 85.3%] but also to identify an active TB infection in a group of TB suspects [sensitivity 76.5%, specificity 87.2%]. These results are significantly better than the much-used screening test based on microscopy. Currently there is no objective diagnosis for metritis. A vet performs the diagnosis based on a number of characteristics such as temperature and appearance of the sample. The eNose proved to be more reliable and objective than a control panel of veterinarians [sensitivity 100%, specificity 91.6%].
ASSOCIATION FOR CONSUMER RESEARCH

sA Theoretical Account for Compulsive Buying: An Application of Escape TheoryRonald J. Faber, University of MinnesotaCompulsive buying has reached the point where it needs to progress from a descriptive stage to an explanatory level of theory development. Escape theory maintains that people with extremely high self-expectations ultimately face failure and painful self-awareness. When these feelings become too extreme, they seek to block out these feelings by becoming completely absorbed in an immediate, concrete task (buying). As a consequence, people fail to consider the long range consequences of their actions and experience fanciful thoughts and magical thinking. Evidence shows that escape theory strongly accounts for findings from compulsive buyers.The Development and Validation of a Scale to Measure Excessive BuyingNancy M. Ridgway, University of RichmondMonika Kukar-Kinney, University of RichmondKent B. Monroe, University of RichmondUsing the theoretical foundations of compulsive buying, obsessive-compulsive disorder and impulse-control disorder, we develop a scale that is geared to measuring excessive buyers who overspend, but are not pathologically ill. Excessive buyers are defined as those who are preoccupied with buying, but who are, at times, able to resist the urge to do so. Pathological buyers, on the other hand are completely unable to control their urges to buy. Using two studies, we show that the scale is both reliable and valid. The scale also shows superiority over other scales developed for use with the general consumer population.Biogenetics, Addiction and Novelty Seeking: A Review of Recent ResearchElizabeth C. Hirschman, Rutgers UniversityThe concepts of novelty seeking and consumption behaviors viewed as addictive, compulsive, and impulsive have received extensive research attention. Less known is that these behaviors have causal roots in the human brain and ultimately the human genetic endowment. Neuroscience and biogenetics researchers have identified the specific neural pathways and the underlying genes which lead individuals to seek out new and exciting stimuli in the environment, become addicted to chemicals, and engage in gambling, extreme sports and impulsive and compulsive buying. Implications for public policy and treatment programs directed toward such destructive consumer behaviors will be discussed.
Evaluation of induced seismicity risk in the Pyhäsalmi mine

Recent increase of induced seismicity and high rock stresses in the Pyhäsalmi mine have proven the need for an analysis of the seismic data and prediction of hazard. Seismic events and other influencing factors are analysed in order to forecast and quantify the level of induced seismicity risk in the Pyhäsalmi mine. The expected maximum event size is found by clustering seismic data using the Quality Threshold and Single Linkage clustering algorithms, and applying the Gutenberg-Richter’s frequency-magnitude relationship. Induced seismicity risk is assessed using the Quantitative Seismic Hazard and Risk Assessment Framework. The potential for induced seismicity is calculated as a function of the maximum local seismic magnitude, rock stresses and strength, local geology, excavation geometry, and ground support capacity. The exposure to hazard is taken into account in order to quantify the level of risk. The assessment is performed on three mining levels at about 1.2 km depth, which are divided into assessment zones. Most of the assessment zones have low seismic risk and only few have an elevated potential of rockburst. The highest risk is found along the northern contact zone of ore and waste rock, adjacent to important mine infrastructure. The critical areas are identified and installation of ground support with increased dynamic capacity is recommended as a risk mitigation strategy.
A Comparative Study of Some Central Notions of ASPIC+ and DeLP

Abstract This paper formally compares some central notions from two well-known formalisms for rule-based argumentation, DeLP and ASPIC+. The comparisons especially focus on intuitive adequacy and inter-translatability, consistency, and closure properties. As for differences in the definitions of arguments and attack, it turns out that DeLP’s definitions are intuitively appealing but that they may not fully comply with Caminada and Amgoud’s rationality postulates of strict closure and indirect consistency. For some special cases, the DeLP definitions are shown to fare better than ASPIC+. Next, it is argued that there are reasons to consider a variant of DeLP with grounded semantics, since in some examples its current notion of warrant arguably has counterintuitive consequences and may lead to sets of warranted arguments that are not admissible. Finally, under some minimality and consistency assumptions on ASPIC+ arguments, a one-to-many correspondence between ASPIC+ arguments and DeLP arguments is identified in such a way that if the DeLP warranting procedure is changed to grounded semantics, then ’s DeLP notion of warrant and ASPIC+ ’s notion of justification are equivalent. This result is proven for three alternative definitions of attack.
UNCERTAINTIES IN SULPHUR AND OXIDISED N DEPOSITION TO WALES ( UK ) MODELLING USING HARM

INTRODUCTION In this paper we quantify the uncertainty associated with deposition estimates for 25 sites in Wales, in the west of the UK, made using HARM (Hull Acid Rain Model), within the Generalised Likelihood Uncertainty Estimation (GLUE) framework of Beven and Binley (1992). GLUE allows uncertainties to be assessed using observed data to condition model predictions. The approach does not attempt to obtain a single parameter set for a given model structure, but recognises that there may be a number of parameter sets which may be identified as ‘behavioural’ in describing the system, based on the fit to the observed data. The goodness of fit is measured by likelihood measures or objective functions. All behavioural parameter sets are used in the calculation of prediction bounds, yielding a range of model responses. Monte Carlo sampling of pre-specified parameter ranges is used to derive combinations of multiple parameters. The model is then run with each randomly chosen parameter set and its performance evaluated as being behavioural (or not) based on the likelihood measures. Model output was initially constrained by comparison with gas concentrations, and wet and dry sulphur and oxidised and reduced nitrogen depositions at 25 sites across Wales for 1995. The robustness of the parameter sets found to perform well for 1995 was then tested by re-running them for wet deposition measured at 44 sites in 1984.
Investigation of Two-Phase Flow in a Hydrophobic Fuel-Cell MicroChannel

This paper presents a quantitative visualization study and a theoretical analysis of two-phase flow relevant to polymer electrolyte membrane fuel cells (PEMFCs) in which liquid water management is critical to performance. Experiments were conducted in an air-flow microchannel with a hydrophobic surface and a side pore through which water was injected to mimic the cathode of a PEMFC. Four distinct flow patterns were identified: liquid bridge (plug), slug/plug, film flow, and water droplet flow under small Weber number conditions. Liquid bridges first evolve with quasi-static properties while remaining pinned; after reaching a critical volume, bridges depart from axisymmetry, block the flow channel, and exhibit lateral oscillations. A model that accounts for capillarity at low Bond number is proposed and shown to successfully predict the morphology, critical liquid volume and evolution of the liquid bridge, including deformation and complete blockage under specific conditions. The generality of the model is also illustrated for flow conditions encountered in the manipulation of polymeric materials and formation of liquid bridges between patterned surfaces. The experiments provide a database for validation of theoretical and computational methods.
Creative Activity 8-2019 ASAP : A Source Code Authorship Program

Source code authorship attribution is the task of determining who wrote a computer program, based on its source code, usually when the author is either unknown or under dispute. Areas where this can be applied include software forensics, cases of software copyright infringement, and detecting plagiarism. Numerous methods of source code authorship attribution have been proposed and studied. However, there are no known easily-accessible and user-friendly programs that perform this task. Instead, researchers typically develop software in an ad hoc manner for use in their studies, and the software is rarely made publicly available. In this paper, we present a software tool called ASAP (A Source Code Authorship Program), which is suitable to be used by either the layperson or the expert. An author can be attributed to individual documents one at a time, or complex authorship attribution experiments can easily be performed on large datasets. In this paper, the interface and implementation of the ASAP tool is presented, and the tool is validated by using it to replicate previously-published authorship attribution experiments.
Inhibition of mTORC 1 induces loss of E-cadherin through AKT / GSK-3 β signaling-mediated upregulation of E-cadherin repressor complexes in non-small cell lung cancer cells

Background: mTOR, which can form mTOR Complex 1 (mTORC1) or mTOR Complex 2 (mTORC2) depending on its binding partners, is frequently deregulated in the pulmonary neoplastic conditions and interstitial lung diseases of the patients treated with rapalogs. In this study, we investigated the relationship between mTOR signaling and epithelial mesenchymal transition (EMT) by dissecting mTOR pathways. Methods: Components of mTOR signaling pathway were silenced by shRNA in a panel of non-small cell lung cancer cell lines and protein expression of epithelial and mesenchymal markers were evaluated by immunoblotting and immunocytochemistry. mRNA level of the E-cadherin repressor complexes were evaluated by qRT-PCR. Results: IGF-1 treatment decreased expression of the E-cadherin and rapamycin increased its expression, suggesting hyperactivation of mTOR signaling relates to the loss of E-cadherin. Genetic ablation of rapamycin-insensitive companion of mTOR (Rictor), a component of mTORC2, did not influence E-cadherin expression, whereas genetic ablation of regulatory-associated protein of mTOR (Raptor), a component of mTORC1, led to a decrease in E-cadherin expression at the mRNA level. Increased phosphorylation of AKT at Ser473 and GSK-3β at Ser9 were observed in the Raptor-silenced NSCLC cells. Of the E-cadherin repressor complexes tested, Snail, Zeb2, and Twist1 mRNAs were elevated in raptor-silenced A549 cells, and Zeb2 and Twist1 mRNAs were elevated in Raptor-silenced H2009 cells. These findings were recapitulated by treatment with the GSK-3β inhibitor, LiCl. Raptor knockdown A549 cells showed increased expression of N-cadherin and vimentin with mesenchymal phenotypic changes. Conclusions: In conclusion, selective inhibition of mTORC1 leads to hyperactivation of the AKT/GSK-3β pathway, inducing E-cadherin repressor complexes and EMT. These findings imply the existence of a feedback inhibition loop of mTORC1 onto mTORC2 that plays a role in the homeostasis of E-cadherin expression and EMT, requiring caution in the clinical use of rapalog and selective mTORC1 inhibitors.
Assessment and Treatment of Behavior Maintained by Automatic Reinforcement

Two subjects diagnosed with autism spectrum disorder (ASD) and related disabilities underwent a functional analysis to ensure hand-clapping was maintained by automatic reinforcement. A secondary analysis (sensory analysis) was conducted to assess the effect of different sensorystimulating items on responding. Finally, a function-based noncontingent reinforcement (NCR) procedure using sensory stimuli was applied to reduce the target behavior, and the schedule of reinforcement was thinned. Results showed a decrease in hand-clapping when the function-based treatment was implemented, and hand-clapping remained at low levels when the schedule of reinforcement was thinned. This research further elucidates how NCR can impact behavior maintained by automatic reinforcement.
Foreword First and foremost , I would like to express my sincere gratitude to my supervisors Prof

The Internet of Things (IoT) technologies are beneficial for both private and businesses. The growth of the technology and its rapid introduction to target fast-growing markets faces security challenges. Machine learning techniques have been recently used in research studies as a solution in securing IoT devices. These machine learning techniques have been implemented successfully in other fields. The objective of this thesis is to identify and analyze existing scientific literature published recently regarding the use of machine learning techniques in securing IoT devices. In this thesis, a systematic literature review was conducted to explore the previous research on the use of machine learning in IoT security. The review was conducted by following a procedure developed in the review protocol. The data for the study was collected from three databases i.e. IEEE Xplore, Scopus and Web of Science. From a total of 855 identified papers, 20 relevant primary studies were selected to answer the research question. The study identified 7 machine learning techniques used in IoT security, additionally, several attack models were identified and classified into 5 categories. The results show that the use of machine learning techniques in IoT security is a promising solution to the challenges facing security. Supervised machine learning techniques have better performance in comparison to unsupervised and reinforced learning. The findings also identified that data types and the learning method affects the performance of machine learning techniques. Furthermore, the results show that machine learning approach is mostly used in securing the network.
University of Groningen Amygdala activation and its functional connectivity during perception of emotional faces in social phobia and panic disorder

Social phobia (SP) and panic disorder (PD) have been associated with aberrant amygdala responses to threat-related stimuli. The aim of the present study was to examine amygdala function and its connectivity with medial prefrontal cortex (mPFC) during emotional face perception in PD and SP, and the role of illness severity. Blood oxygen level dependent responses while perceiving emotional facial expressions were compared in 14 patients with PD, 17 patients with SP, 8 patients with comorbid PD and SP, and 16 healthy controls. We found that PD, but not SP, was associated with amygdala and lingual gyrus hypoactivation during perception of angry, fearful, happy and neutral faces, compared to healthy participants. No significant effect of PD and SP diagnoses was found on amygdalaemPFC connectivity. A positive correlation of anxiety symptom severity was found on amygdala-dorsal anterior cingulate and dorsal mPFC connectivity during perception of fearful faces. Amygdala hypoactivation suggests reduced responsiveness to positive and negative emotional faces in PD. Symptom severity, but not the presence of PD and SP diagnosis per se, explains most of the abnormalities in amygdalaemPFC connectivity during perception of fearful faces. 2013 Elsevier Ltd. All rights reserved.