Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluorescence-Based Determination of Olive Oil Quality Using an Endoscopic Smart Mobile Spectrofluorimeter

The application of self-contained field-portable, internet connected spectroscopic diagnostics in food analysis using a fibre endoscopic smart fluorimeter is reported. A UV-induced fluorescence is used to measure the quality of olive oils, distinguishing between extra virgin and others within a smartphone platform. When excited at <inline-formula> <tex-math notation="LaTeX">$\lambda \sim ~370$ </tex-math></inline-formula> nm, the extra virgin olive oil fluoresces red at <inline-formula> <tex-math notation="LaTeX">$\lambda \sim ~670$ </tex-math></inline-formula> nm. Notably, other oils do not fluoresce red but rather blue, consistent with degradation of the chlorophyll in the oil. Artificial refinement employed in some of the commercial products removes the red emission providing a simple method for distinguishing extra virgin olive oil from all other oils. A smartphone endoscopic fluorimeter is designed and constructed that measures the emission band <inline-formula> <tex-math notation="LaTeX">$\Delta \lambda \sim $ </tex-math></inline-formula> (400– 700) nm with <inline-formula> <tex-math notation="LaTeX">$\lambda \sim ~370$ </tex-math></inline-formula> nm excitation. The instrument is used to characterise the fluorescence of the oils. Photo-degradation over time for extra virgin olive oil under room lights is observed, demonstrating the origin for the decomposition of extra virgin olive oil in transparent bottles. Extra virgin olive oils are also susceptible to thermal degradation more than refined oils.
Repeatability analysis improves the reliability of behavioral data

Reliability of data has become a major concern in the course of the reproducibility crisis. Especially when studying animal behavior, confounding factors such as novel test apparatus can lead to a wide variability of data. At worst, effects of novelty or stress related behavior can mask treatment effects and the behavioral data may be misinterpreted. Habituation to the test situation is a common practice to circumvent novelty induced increases in variance and to improve the reliability of the respective measurements. However, there is a lack of published empirical knowledge regarding reasonable habituation procedures and a method validation seems to be overdue. This study aimed at setting up a simple strategy to increase reliability of behavioral data. Therefore, exemplary data from mice tested in an Open Field (OF) arena were used to elucidate the potential of habituation and how reliability of measures can be confirmed by means of a repeatability analysis using the software R. On seven consecutive days, male C57BL/6J, BALB/cJ and 129S1/SvImJ mice were tested in an OF arena once daily and individual mouse behavior (distance travelled, average activity) was recorded. A repeatability analysis was conducted in order to estimate the reliability of measured animal behavior with regard to repeated trials of habituation. Our data analysis revealed that monitoring animal behavior during habituation is important to determine when individual differences of the measurements are stable. Here, the mixed effect model framework proved to be a powerful tool for estimating repeatability values. Repeatability values from distance travelled and average activity increased over the habituation period, revealing that around 60 % of the variance of the data can be explained by individual differences between mice. The first day of habituation was statistically significantly different from the following 6 days in terms of distance travelled and average activity. A habituation period of three days appeared to be sufficient in this study. Overall these results emphasize the importance of habituation and in depth analysis of habituation data to define the correct starting point of the experiment for improving the reliability and reproducibility of experimental data.
High spatial turnover in springtails of the Cape Floristic Region

The extraordinary diversity of plants across the Cape Floristic Region is characterized by considerable species turnover among sites. Phytophagous insects show similarly high turnover, but their patterns are closely coupled to those of their hosts. If the mechanisms underlying high plant turnover are not unique to plants, similar patterns of turnover should also be seen in non‐herbivorous arthropod groups. We tested this hypothesis using new data for the Collembola fauna of the Fynbos biome.
The Role of Illness Identity in Assertive Community Treatment

Assertive community treatment (ACT) provides comprehensive clinical services, including vocational rehabilitation, to individuals with psychiatric disorders for which traditional community mental health services are insufficient. ACT is an evidence-based intervention yielding many positive outcomes, yet service recipients continue to struggle with workforce involvement. The purpose of this study is to determine whether internalized stigma, psychiatric hospitalization, and psychiatric symptoms are associated with work-related self-efficacy among ACT service recipients. A total of 72 individuals with severe mental illness were recruited from ACT programs in three counties in a Mid-Atlantic state. Multiple linear regression was conducted to examine the relationship between work-related self-efficacy and the independent variables of internalized stigma, psychiatric hospitalization, and psychiatric symptoms. Higher internalized stigma scores were negatively associated with work-related self-efficacy (β = −.31, t = −2.32, p < .05), while psychiatric hospitalization in the past year was positively associated with work-related self-efficacy (β = .22−.27, t = −2.13, p < .05). Findings from this study suggests internalized stigma to be an important recovery variable requiring the attention of ACT team members when preparing individuals for work, while countering the assumption that recent hospitalization is a barrier to work-related self-efficacy.
Efficient speaker diarization and low-latency speaker spotting

Speaker diarization (SD) involves the detection of speakers within an audio stream and the intervals during which each speaker is active, i.e. the determination of ‘who spoken when’. The first part of the work presented in this thesis exploits an approach to speaker modelling involving binary keys (BKs) as a solution to SD. BK modelling is efficient and operates without external training data, as it operates using test data alone. The presented contributions include the extraction of BKs based on multi-resolution spectral analysis, the explicit detection of speaker changes using BKs, as well as SD fusion techniques that combine the benefits of both BK and deep learning based solutions. The SD task is closely linked to that of speaker recognition or detection, which involves the comparison of two speech segments and the determination of whether or not they were uttered by the same speaker. Even if many practical applications require their combination, the two tasks are traditionally tackled independently from each other. The second part of this thesis considers an application where SD and speaker recognition solutions are brought together. The new task, coined low latency speaker spotting (LLSS), involves the rapid detection of known speakers within multi-speaker audio streams. It involves the re-thinking of online diarization and the manner by which diarization and detection sub-systems should best be combined.
Rare but Long-lasting Liquidity Traps and Fiscal Stimulus

A DSGE model with (i) state-dependent pricing and (ii) history-dependent monetary policy that compensates for lost opportunities of cutting the nominal interest rate due to a binding effective zero lower bound (ZLB) generates rare but long-lasting liquidity traps with endogenous transitions between the traps and normal times. Dynamic government spending multipliers (GSMs) are typically above unity in the liquidity traps but are uniformly below unity in normal times. Without (i) or (ii), the model generates only short-lived ZLB events while producing below-unity GSMs irrespective of the state of the economy.
Distributed resilient estimation over sensor networks for nonlinear time‐delayed systems with stochastic perturbations

This paper is concerned with the distributed resilient estimation problem for a class of nonlinear time‐delayed systems subject to stochastic perturbations. The plant and the measurements are disturbed by two Gaussian white stochastic processes with known statistical information, respectively. In addition, a resilient estimator is designed for each node by means of the parameter uncertainties and Bernoulli‐distributed random variables. Then, a novel exponential‐bounded performance index is put forward to measure the disturbance rejection level of the distributed estimators against the external disturbances and the impact of the initial values. A new vector dissipation definition including multiple vectors of energy storage functions is established to deal with the time‐delay estimation error dynamics. Within the framework of local performance analysis inspired by this new definition of vector dissipation, sufficient conditions in terms of recursive linear matrix inequalities are constructed for each node to guarantee the desirable performance index. Next, a local optimization problem subject to a set of recursive linear matrix inequalities is presented for each node to minimize the upper bound in the performance index, where the calculations can be conducted on every node in a distributed manner and the estimator gains are also calculated. Finally, an illustrative simulation example is provided to verify the applicability of the proposed estimators.
Mathematical modeling of directed acyclic graphs to explore competing causal mechanisms underlying epidemiological study data

1Accurately estimating the effect of an exposure on an outcome requires understanding how variables relevant to a study question are causally related to each other. Directed acyclic graphs (DAGs) are used in epidemiology to understand causal processes and determine appropriate statistical approaches to obtain unbiased measures of effect. Compartmental models (CMs) are also used to represent different causal mechanisms, by depicting flows between disease states on the population level. In this paper, we extend a mapping between DAGs and CMs to show how DAG–derived CMs can be used to compare competing causal mechanisms by simulating epidemiological studies and conducting statistical analyses on the simulated data. Through this framework, we can evaluate how robust simulated epidemiological study results are to different biases in study design and underlying causal mechanisms. As a case study, we simulated a longitudinal cohort study to examine the obesity paradox: the apparent protective effect of obesity on mortality among diabetic ever-smokers, but not among diabetic never-smokers. Our simulations illustrate how study design bias (e.g., reverse causation), can lead to the obesity paradox. Ultimately, we show the utility of transforming DAGs into in silico laboratories within which researchers can systematically evaluate bias, and inform analyses and study design.
Inclusion of the Children with Autism Spectrum Disorder in a Private Mainstream School in Abu Dhabi: An Investigative Study

The children who have Autism Spectrum Disorder (ASD) are the individuals who are facing difficulties and challenges in the education and social life regardless of the background. This case study aims to investigate the effectiveness of the inclusion of the children with Autism Spectrum Disorder in the United Arab Emirates. The case study was conducted in a private mainstream school in Abu Dhabi, the capital city of UAE, over a period of six weeks on four students with Autism Spectrum Disorder. The effectiveness of the inclusion has been investigated over four main skills (reading, writing, listening, speaking). At the end of this study, a set of recommendations has been mentioned to improve the inclusion in UAE. Early identification and accurate diagnosis of autism improve the likelihood of favorable outcomes for children with Autism Spectrum Disorder (ASD). Thus, early identification and diagnosis of autism are gaining global attention. There are needs to avoid the negative implications of lack of diagnosis, misdiagnosing or over-diagnosing children with autism. The study aspires to contribute in improving the services for children in the United Arab Emirates (UAE) by examining the current situation, parents’ views, and other stakeholders’ views. The objective is to provide information that will help design better procedures in the country. A combination of surveys, interviews, and focus groups are used as sources of data for the study. This provides a view of the missing components and the challenges that is faced in the process. It provides insights into the difficulties, struggles, and gaps in the current system that need to be addressed to improve the services in the future. The study of the literature, identifying gaps in the development of diagnostic processes, diagnostic criteria, training and educating professionals need to be addressed to develop the process. This research pointed out concerns related to certain aspects of the service in the UAE. Some recommendations are outlined in the study to better enhance the services and to provide effective services for children with autism.
Combined molecular and morphological data provide insights into the evolution and classification of Chilocorini ladybirds (Coleoptera: Coccinellidae)

Ladybirds of the cosmopolitan tribe Chilocorini prey mainly on coccids and include several important biocontrol agents. The phylogenetic relationships of Chilocorini are poorly known. In this paper, we provide a phylogenetic reconstruction of Chilocorini containing all 27 genera based on five molecular markers and 86 adult morphological characters. Morphological character states were mapped on the combined data tree from Bayesian inference to analyse morphological traits of each genus. Sixteen morphological characters were selected to reconstruct the ancestral states using maximum parsimony and maximum likelihood methods. Divergence times were estimated based on the relaxed molecular clock approach. Our results indicate that Chilocorini, excluding Chilocorellus Miyatake, is monophyletic and closely related to Plotinini. The crown group Chilocorini was estimated to date back to the Middle Cretaceous. Anisorcus Crotch, Egius Mulsant, Phaenochilus Weise and Simmondsius Ahmad & Ghani are synonymized here with Chilocorus Leach (syn.n.). The genus Chilocorellus is excluded from Chilocorini. The split of current genera was estimated to have occurred during the Middle Paleogene to Late Paleogene.
Quantitative PET-CT Perfusion Imaging of Prostate Cancer

Functional imaging of F-Fluorocholine PET holds promise for the detection of dominant prostatic lesions. Quantitative parameters from PET-CT Perfusion may be capable of measuring choline kinase activity, which could assist in identification of the dominant prostatic lesion for more accurate targeting of biopsies and radiation dose escalation. The objectives of this thesis are: 1) investigate the feasibility of using venous TACs in quantitative graphical analysis, and 2) develop and test a quantitative PET-CT Perfusion imaging technique that shows promise for identifying dominant prostatic lesions. Chapter 2 describes the effect of venous dispersion on distribution volume measurements with the Logan Plot. The dispersion of venous PET curves was simulated based on the arterio-venous transit time spectrum measured in a perfusion CT study of the human forearm. The analysis showed good agreement between distribution volume measurements produced by the arterial and venous TACs. Chapter 3 details the mathematical implementation of a linearized solution of the 3Compartment kinetic model for hybrid PET-CT Perfusion imaging. A noise simulation determined the effect of incorporating CT perfusion parameters into the PET model on the accuracy and variability of measurements of the choline kinase activity. Results indicated that inclusion of CT perfusion parameters known a priori can significantly improve the accuracy and variability of imaging parameters measured with PET. Chapter 4 presents the implementation of PET-CT Perfusion imaging in a xenograft mouse model of human prostate cancer. Image-derived arterial TACs from the left ventricle were
Chemical loss processes of isocyanic acid, HNCO, in the atmosphere

Abstract. The impact of chemical loss processes of isocyanic acid was studied by a combined theoretical and modeling study. The potential energy surfaces of the reactions of HNCO with OH and NO3 radicals, Cl atoms, and ozone, were studied using high-level CCSD(T)/CBS(DTQ)//M06-2X/aug-cc-pVTZ quantum chemical methodologies, followed by TST theoretical kinetic predictions of the rate coefficients at temperatures of 200–3000 K. It was found that the reactions are all slow in atmospheric conditions, with k(300 K) ≤ 7 × 10−16 cm3 molecule−1 s−1; the predictions are in good agreement with earlier experimental work, where available. The reverse reactions of NCO radicals, of importance mostly in combustion, were also examined briefly. The global model confirms that gas phase chemical loss of HNCO is a negligible process, contributing less than 1 %. Removal of HNCO by clouds and precipitation is a larger sink, contributing for about 10 % of the total loss, while globally dry deposition is the main sink, accounting for ~ 90 %. The global simulation also shows that due to its long chemical lifetime in the free troposphere, HNCO can be efficiently transported into the UTLS by deep convection events. Average daily concentrations of HNCO are found to rarely exceed levels considered potentially toxic, though locally instantaneous toxic levels are expected.the free troposphere, HNCO can be efficiently transported into the UTLS by deep convection events. Average daily concentrations of HNCO are found to rarely exceed levels considered potentially toxic, though locally instantaneous toxic levels are expected.
Affective curriculum to target perfectionism and associated outcomes in pre-adolescent gifted and typical students

DISSERTATION: Affective Curriculum to Target Perfectionism and Associated Outcomes in Pre-Adolescent Gifted and Typical Students STUDENT: Marlyssa Rae Fillmore DEGREE: Doctor of Philosophy COLLEGE: Teacher’s College DATE: July 2019 PAGES: 115 This study has covered the development, implementation, and evaluation of an affective curriculum designed specifically for gifted and typical students in 3, 4, and 5 grades. The curriculum was designed to decrease levels of perfectionism, depression, and anxiety in students while simultaneously increasing life satisfaction. This study first explores the relationship between the studied variables and their impact on student well-being. Details pertaining to the construction and implementation of the intervention are covered and results are reviewed. While no significant differences were found between the treatment and control groups, secondary findings pertaining to grade-level and gifted status are explored. Implications for future study and the impact on the field of school psychology are discussed.
Simulation-based investigation of a marine dual-fuel engine

ABSTRACT Recent developments have rendered the Dual Fuel (DF) engines an attractive alternative solution for achieving cost-efficient compliance to environmental regulations. The present study focuses on the safety investigation of a marine DF engine in order to identify potential safety implications. This investigation is based on an integrated engine model, which was developed in GT-ISE™ software and is capable of predicting both the engine steady-state behaviour and transient response. The model includes the engine thermodynamic simulation module as well as the engine control system functional module; the latter is responsible for implementing the ordered load changes and the operating mode switching. The developed model is first validated against available published data and subsequently used to simulate several test cases with fuel changes, from gas to diesel and diesel to gas with rapid and with delayed wastegate valve operation. The derived simulation results are used to investigate the potential safety implications that can arise during the engine operation. The results demonstrate that the engine–turbocharger matching as well as the wastegate control are critical parameters for ensuring the compressor surge free operation during gas to diesel modes transition. Abbreviations: 0D: zero-dimensional; 1D: one-dimensional; BMEP: brake mean effective pressure; CO2: carbon dioxide; DF: dual fuel; D/G: diesel generator; DTG: diesel to gas fuel modes switching; ECA: emission control area; ECS: engine control system; EEDI: energy efficiency design index; GTD: gas to diesel modes switching; HFO: heavy fuel oil; IMO: International Maritime Organization; LFO: light fuel oil; LNG: liquefied natural gas; MCR: maximum continuous rating; NOx: nitrogen oxides; PHA: preliminary hazard analysis; PI: proportional–integral; SOx: sulphur oxides; TC: turbocharger; WG: wastegate; λ: air–fuel equivalence ratio
Bayesian Nonparametric Monotone Regression of Dynamic Latent Traits in Item Response Theory Models

Parametric methods, such as autoregressive models or latent growth modeling, are usually inflexible to model the dependence and nonlinear effects among the changes of latent traits whenever the time gap is irregular and the recorded time points are individually varying. Often in practice, the growth trend of latent traits is subject to certain monotone and smooth conditions. To incorporate such conditions and to alleviate the strong parametric assumption on regressing latent trajectories, a flexible nonparametric prior has been introduced to model the dynamic changes of latent traits for item response theory models over the study period. Suitable Bayesian computation schemes are developed for such analysis of the longitudinal and dichotomous item responses. Simulation studies and a real data example from educational testing have been used to illustrate our proposed methods.
Attachment orientations and sleep patterns: The moderating role of exchanges with spouse

The objective of the study was to investigate habitual nightly sleep patterns in the context of daily accounts of relationships with bed partners utilizing the attachment theory framework. Negative exchanges with a spouse are stressful and presumably activate the attachment system. This will differently affect individuals with high and low levels of attachment avoidance and anxiety orientations, affecting their sleep patterns. Seventy-seven teachers in committed romantic relationships (mean age = 42.53 years, 89.3% married) participated. They first completed the Experience in Close Relationships–Revised instrument, indicating their attachment avoidance and anxiety orientations, and then participated in a 4-day diary study, reporting daily levels of negative exchanges with a spouse. They also wore an actigraph (activity monitor) during the nighttime to assess their sleep patterns. Mixed-model analyses revealed that respondents high in attachment avoidance had later bedtimes and shorter sleep duration following days high in negative behavioral exchanges with their spouses. In addition, respondents high in attachment avoidance had longer sleep latency and more waking episodes during the night, regardless of levels of negative exchanges. Individuals high in attachment anxiety had more waking episodes during the night after negative emotional exchanges with a spouse; the opposite pattern emerged for individuals low in attachment anxiety. Findings demonstrate the relevance of attachment orientations and the moderating effects of negative exchanges with a spouse on sleep patterns.