Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Multi-instance Enriched Image Representations via Non-greedy Ratio Maximization of the l1-Norm Distances

Multi-instance learning (MIL) has demonstrated its usefulness in many real-world image applications in recent years. However, two critical challenges prevent one from effectively using MIL in practice. First, existing MIL methods routinely model the predictive targets using the instances of input images, but rarely utilize an input image as a whole. As a result, the useful information conveyed by the holistic representation of an input image could be potentially lost. Second, the varied numbers of the instances of the input images in a data set make it infeasible to use traditional learning models that can only deal with single-vector inputs. To tackle these two challenges, in this paper we propose a novel image representation learning method that can integrate the local patches (the instances) of an input image (the bag) and its holistic representation into one single-vector representation. Our new method first learns a projection to preserve both global and local consistencies of the instances of an input image. It then projects the holistic representation of the same image into the learned subspace for information enrichment. Taking into account the content and characterization variations in natural scenes and photos, we develop an objective that maximizes the ratio of the summations of a number of l1-norm distances, which is difficult to solve in general. To solve our objective, we derive a new efficient non-greedy iterative algorithm and rigorously prove its convergence. Promising results in extensive experiments have demonstrated improved performances of our new method that validate its effectiveness.
Lexical access across talkers

ABSTRACT The current paper examined whether lexical access might (ever) cross talker boundaries. In four cross-modal priming experiments, listeners made visual lexical decisions after hearing an auditory word or word pair. On some trials, the auditory signal was produced by a single talker; on other trials, a talker gender change occurred in the middle of the auditory sequence. Participants demonstrated priming for items crossing both word boundaries and talker changes: after hearing a male talker say my and a female talker say great, participants showed a speeded response to “geese” (related to “migrate”). Priming was based on the combination of syllables across talkers, not driven simply by the first word. Findings suggest that acoustic cues indicating multiple talkers are insufficient to disrupt lexical access, and activation of lexical representations is not limited to those occurring within a single-talker stream. This provides support for models that do not involve explicit pre-lexical segmentation.
ENDOPHYTIC BACTERIA CONTROLLING FUSARIUM OXYSPORUM AND RHIZOCTONIA SOLANI IN SOLANUM TUBEROSUM

This study was conducted to test multiple endophytic bacteria as biological control agents against Rhizoctonia solani and Fusarium oxysporum. A total of 26 endophytic bacteria were isolated from potato plants. Two strains of Bacillus amyloliquefaciens (strain21 and strain53) were found to be potential biological control agents based on their radial growth inhibition percentage (RGIP) in dual culture test. The biocontrol potential of the two most effective antagonist strains was evaluated in potato plants under greenhouse conditions against R. solani and F. oxysporum. As a result, both bacteria promoted growth and development of the crop by increasing chlorophyll content, biomass fresh weight, root weight, stem diameter, plant height and crop yield. Both bacteria favored the health of potato plants in 909.09% against R. solani and 303.03% against F. oxysporum. This study suggests the use of endophytic bacteria to minimize losses caused by wilt diseases and root rot in greenhouses.
Integration of the Multi-DOA Estimation Functionality to Human-Robot Interaction

Sound source localization is important in human interaction, such as in locating the origin of long-distance calls or facing other humans while in a conversation. It is of interest to apply such functionality to the core of human-robot interaction (HRI) and investigate its benefits, if any. In this paper, we propose three strategies for how to integrate the functionality of multiple directions-of-arrival (multi-DOA) estimation with a common scenario, in which the robot acts as a waiter while applying audio source localization. The proposed strategies are: a) the robot locates calls from users at a relatively long distance; b) the robot faces the user when taking the order; and c) the robot announces whether the acoustic environment is not conducive to understanding a speech command (mainly where more than one user speaks at once). It was seen that users react favourably to the functionality, and that it even has a noticeable influence on the success of the interaction.
Investigation of possible risk factors in the development of seasonal allergic conjunctivitis.

AIM To analyze the possible risk factors in the development of seasonal allergic conjunctivitis (SAC) through an evaluation of skin allergy tests and data obtained from questionnaires. METHODS The study included a total of 75 SAC patients and 71 control subjects without SAC diagnosis who were admitted to the Abant Izzet Baysal University Medical Faculty Ophthalmology Clinic between March 2016 and December 2016. Skin prick tests were performed for all participants. Serum levels of total IgE and 25-OH vitamin D were also measured. In the tear, total IgE levels were measured. Moreover, possible risk factors for the onset of SAC (smoking, paracetamol exposure, vitamin D supplementation and environmental factors etc.) were examined for all patients by both prenatal and postnatal aspects. RESULTS The patients with SAC were found to have a history of maternal paracetamol exposure during the prenatal period. Likewise, in the same patient group, the duration of postnatal vitamin D supplementation was shorter (P<0.001). However, no significant correlation was found between SAC and maternal antibiotic exposure, maternal smoking, the mode of delivery and birth weight, as well as presence of pets. Moreover, patients with SAC were more likely to have asthma, allergic rhinitis and oral allergy syndrome. We have also found that SAC patients' mothers and siblings were more likely to have allergic conjunctivitis. Likewise, their fathers were more likely to have allergic rhinitis. CONCLUSION Prenatal maternal paracetamol exposure and shorter duration of vitamin D supplementation in the postnatal period may play a role in development of SAC. Therefore prevention of unnecessary gestational paracetamol intake and vitamin D supplementation during infancy could potentially reduce the onset and development of SAC.
Some Biological Parameters of Round Herring , Etrumeus teres ( De Kay , 1842 ) in the Gulf of Antalya ( Mediterranean Sea )

Etrumeus teres, whose population in the Gulf of Antalya is gradually increasing, is a fish species which migrates from the Red Sea to the Eastern Mediterranean. The settling of the E. teres species in the Mediterranean makes a close observation of its population necessary from the point of view of the possible competition into which it may enter with other species of the eco-system. This study was carried out due to the lack of sufficient research on this subject. The length, growth, age composition, condition factors, and sex ratio of E. teres were studied on the basis of 438 specimens from the Gulf of Antalya. Females made up 55.7% and males 44.3% of the species. Min. and max. standard length was 9.5-22.5 cm in females, 9.5-21.5 cm in males. In the population the average standard length values according to age for females, males and all specimens combined at age I were 14.50, 13.96, 14.23 cm respectively; at age II these were 17.91, 17.90, 17.90 cm; at age III they were 20.89, 20.87, 20.88 cm The length-weight relationships estimated for males, females and all fish were W= 0.00834 L, W= 0.00787L and W= 0.00942L respectively. Growth parameter estimates L∞= 33.77 cm, K= 0.20, t0 = -1.6313 were calculated according to von Bertalanffy for all fish. Individuals were between I and III years old and 44.47% of them were I year old and 47.91% of them were II years old. The condition factor was found to be significant in relation to age and months, but nonsignificant
Poole-Frenkel (PF) effect high field saturation

An improved Poole Frenkel (PF) effect, based upon a rigorous methodological approach, is proposed. The chosen model is stated precisely, emphasis being made explicitly on the subtending hypotheses. A systematic reference to Fermi-Dirac function, allows to establish quantitatively the concept of PF saturation. The resulting general theory integrates, as particular applications, the previous one-dimensional PF theories.
A Survey of Context-Aware Pervasive Applications : From Development Support to Quality Assurance PhD Qualifying Exam Report

Pervasive applications aim to provide unobtrusive and reliable computing services by seamlessly integrating devices into end users’ everyday life. As an important branch of pervasive computing, context-aware applications continuously sense environmental changes and automatically adapt their behaviors. In recent years, such kind of computing paradigm is becoming more and more popular with the proliferation of versatile mobile devices and increasing deployment of pervasive infrastructures. However, due to the distributed nature and heterogeneity of context sources, building and maintaining a context-aware application is a non-trivial task. Researchers have identified quite a few critical challenges for systematic engineering of these applications, ranging from modeling to quality assurance. In this survey, we focus on reviewing existing research works related to development support and quality assurance. For development support, we will introduce some famous middleware infrastructures, development toolkits as well as typical design strategies. For quality assurance, we will cover context quality enhancement, testing and software model checking approaches. In the final section of this survey, we will point out some promising research directions in this area. Student: Yepang Liu Supervisor: Shing-Chi Cheung Submission Date: December 28, 2011
A lexicon-based method for Sentiment Analysis using social network data

In the era of social media, use of social networking data to study customers’ attitudes toward brands, products, services, or events has become an increasingly dominant trend in business strategic management research. Sentiment analysis, which is also called opinion mining, is a field of study that aims at extracting opinions and sentiments from natural language text using computational methods. It can assist in search engines, recommender systems and market research. With the growth of the internet, numerous business websites have been deployed to support online shopping and booking services as well as to allow online reviewing and commenting the services in forms of either business forums or social networks. Mining opinion automatically using the reviews from such online platforms is not only useful for customers to seek for advice, but also necessary for business to understand their customers and to improve their services. There are currently several approaches for sentiment analysis. In this research, we proposed a lexiconbased method using sentiment dictionaries with a heuristic method for data pre-processing. We showed that our method outperformed state-of-the-art lexicon-based methods. Keywords— sentiment analysis; text mining; social network; natural language processing; strategic management
Machine Learning Methods for Malware Detection and Classification

Malware detection is an important factor in the security of the computer systems. However, currently utilized signature-based methods cannot provide accurate detection of zero-day attacks and polymorphic viruses. That is why the need for machine learning-based detection arises. The purpose of this work was to determine the best feature extraction, feature representation, and classification methods that result in the best accuracy when used on the top of Cuckoo Sandbox. Specifically, k-Nearest-Neighbors, Decision Trees, Support Vector Machines, Naive Bayes and Random Forest classifiers were evaluated. The dataset used for this study consistsed of the 1156 malware files of 9 families of different types and 984 benign files of various formats. This work presents recommended methods for machine learning based malware classification and detection, as well as the guidelines for its implementation. Moreover, the study performed can be useful as a base for further research in the field of malware analysis with machine learning methods.
Mean Field Linear-Quadratic-Gaussian (LQG) Games of Forward-Backward Stochastic Differential Equations

This paper studies a new class of dynamic optimization problems of large-population (LP) system which consists of a large number of negligible and coupled agents. The most significant feature in our setup is the dynamics of individual agents follow the forward-backward stochastic differential equations (FBSDEs) in which the forward and backward states are coupled at the terminal time. This current paper is hence different to most existing large-population literature where the individual states are typically modeled by the SDEs including the forward state only. The associated mean-field linear-quadratic-Gaussian (LQG) game, in its forward-backward sense, is also formulated to seek the decentralized strategies. Unlike the forward case, the consistency conditions of our forward-backward mean-field games involve six Riccati and force rate equations. Moreover, their initial and terminal conditions are mixed thus some special decoupling technique is applied here. We also verify the $\epsilon$-Nash equilibrium property of the derived decentralized strategies. To this end, some estimates to backward stochastic system are employed. In addition, due to the adaptiveness requirement to forward-backward system, our arguments here are not parallel to those in its forward case.
SedFoam-2.0: a 3-D two-phase flow numerical model for sediment transport

Abstract. In this paper, a three-dimensional two-phase flow solver, SedFoam-2.0, is presented for sediment transport applications. The solver is extended from twoPhaseEulerFoam available in the 2.1. 0 release of the open-source CFD (computational fluid dynamics) toolbox OpenFOAM. In this approach the sediment phase is modeled as a continuum, and constitutive laws have to be prescribed for the sediment stresses. In the proposed solver, two different intergranular stress models are implemented: the kinetic theory of granular flows and the dense granular flow rheology μ(I). For the fluid stress, laminar or turbulent flow regimes can be simulated and three different turbulence models are available for sediment transport: a simple mixing length model (one-dimensional configuration only), a k − e, and a k − ω model. The numerical implementation is demonstrated on four test cases: sedimentation of suspended particles, laminar bed load, sheet flow, and scour at an apron. These test cases illustrate the capabilities of SedFoam-2.0 to deal with complex turbulent sediment transport problems with different combinations of intergranular stress and turbulence models.
PLANT ROOT EFFECTS ON SOIL ERODIBILITY, SPLASH DETACHMENT, SOIL STRENGTH, AND AGGREGATE STABILITY

The influence of dead roots on soil erodibility, splash detachment, and aggregate stability was studied in the laboratory using a rainfall simulator on a Mexico silt loam (fine, montmorillnitic, mesic, Udollic Ochraqualf). Soil was collected from four cropping treatments including alfalfa, Canada bluegrass, corn, and soybeans. Rainfall of 64 mm h–1 intensity was applied for 1 h during the first day. On the second day, a 30-min run of constant intensity (64 mm h–1) was applied which was followed by four 15-min storms at intensities of 25, 100, 50, and 75 mm h–1. Dead root mass and dead root length in the 0- to 0.15-m depth from the perennial crops (alfalfa and bluegrass) were much higher than those from annual row crops (corn and soybean). There was almost a five-fold difference in root mass and root length between alfalfa and soybeans. The study showed that dead roots did not affect runoff, but had significant effect (p <0.05) on soil loss and sediment concentrations. However, the differences in soil loss and sediment concentrations were small relative to the differences in dead root mass and dead root length. Interrill erodibility (Ki) decreased as dead root mass and dead root length increased. There were exponential relationships between Ki and dead root mass, and Ki and dead root length. Dead roots had significant effects (p <0.05) on soil shear strength, aggregate index, and dispersion ratio. Soil shear strength and aggregate index from alfalfa and Canada bluegrass were approximately 20 and 50%, respectively, higher than those from corn and soybean. Dispersion ratios from alfalfa and bluegrass were about 30% lower than those from corn and soybean. There was no significant difference (p <0.05) in soil splash among the crops. Splash detachment was highest during the initial 10 min of the simulation and then decreased exponentially.
Emulation of dynamic computer models with multivariate output

This preliminary report describes work carried out as part of work package 1.2 of the MUCM research project. The report is split in two parts: the ? rst part (Sections 1 and 2) summarises the state of the art in emulation of computer models, while the second presents some initial work on the emulation of dynamic models. In the ? rst part, we describe the basics of emulation, introduce the notation and put together the key results for the emulation of models with single and multiple outputs, with or without the use of mean function. In the second part, we present preliminary results on the chaotic Lorenz 63 model. We look at emulation of a single time step, and repeated application of the emulator for sequential predic- tion. After some design considerations, the emulator is compared with the exact simulator on a number of runs to assess its performance. Several general issues related to emulating dynamic models are raised and discussed. Current work on the larger Lorenz 96 model (40 variables) is presented in the context of dimension reduction, with results to be provided in a follow-up report. The notation used in this report are summarised in appendix.
Estimation Methods Comparison of SVAR Models with a Mixture of Two Normal Distributions

This paper addresses the issue of obtaining maximum likelihood estimates of parameters for structural VAR models with a mixture of distributions. Hence the problem does not have a closed form solution, numerical optimization procedures need to be used. A Monte Carlo experiment is designed to compare the performance of four maximization algorithms and two estimation strategies. It is shown that the EM algorithm outperforms the general maximization algorithms such as BFGS, NEWTON and BHHH. Moreover, simplification of the problem introduced in the two steps quasi ML method does not worsen small sample properties of the estimators and therefore may be recommended in the empirical analysis.
Rare earth based nanostructured materials: synthesis, functionalization, properties and bioimaging and biosensing applications

Abstract Rare earth based nanostructures constitute a type of functional materials widely used and studied in the recent literature. The purpose of this review is to provide a general and comprehensive overview of the current state of the art, with special focus on the commonly employed synthesis methods and functionalization strategies of rare earth based nanoparticles and on their different bioimaging and biosensing applications. The luminescent (including downconversion, upconversion and permanent luminescence) and magnetic properties of rare earth based nanoparticles, as well as their ability to absorb X-rays, will also be explained and connected with their luminescent, magnetic resonance and X-ray computed tomography bioimaging applications, respectively. This review is not only restricted to nanoparticles, and recent advances reported for in other nanostructures containing rare earths, such as metal organic frameworks and lanthanide complexes conjugated with biological structures, will also be commented on.
The Gel Phase

The lipid bilayer is a thermodynamic system that transitions from the relatively disordered liquid phase to the relatively ordered gel or solid-phase when enough heat is removed from the system [1]. In this page we will detail the gel phase of the lipid bilayer. Biological plasma membranes express a plethora of unique lipids, sterols, and proteins and exhibit greater complexity than model lipid bilayer systems. At temperatures above the melting point (Tm) the lipid bilayer exists in the liquid phase while at temperatures below Tm, the lipid bilayer enters the gel phase. In the gel phase, the lipid bilayer undergoes a fundamental molecular reorganization characterized by an increase in order, a loss of lateral mobility within a given leaf of the bilayer as well as a change in acyl chain configuration within a single lipid molecule, and a change in the broad topology of the membrane [1, 2, 3].
Dynamic Choropleth Maps – Using Amalgamation to Increase Area Perceivability

Choropleths are a common and useful way of depicting area-coupled data on a geo-spatial map. One advantage they provide is combining area-based data accurately with geo-space. However perceptual problems arise when areas are too small, i.e when they only cover a few pixels or less. This is a very common occurrence when zooming or in densely populated areas like capital cities. We present a novel algorithm that ensures the user is able to observe area-based data coupled to geo-space based on their interactive level of zoom without distorting the original geo-spatial map. This is resolved by building a hierarchical data structure in which each area and its data is merged with one of its smallest neighbor recursively until only one polygon covers each contiguous region. The benefits are that the viewer can always view area-based data contained in the map regardless of how small any individual area becomes during interactive zooming. We break down each step of the algorithm and provide pseudo-code to enable reproducibility. We also discuss unique test cases that challenge the robustness of the algorithm with 30,000 polygons and 4,652,800 vertices as well as the performance.
The role of parenting and attachment in identity style development

The present study set investigates the role of the parent-child relationship in identity formation using a sample of 264 students collected from two high schools in the central Florida area. Maternal responsiveness fosters both the informational and normative identity style, as well as positive attachment. Such results suggest that a warm and loving maternal figure allows children to feel safe in their environment, which encourages exploration. Furthermore, positive attachment was found to significantly predict a normative identity style. Despite both responsiveness and attachment independently predicting a normative identity style, issues were raised in regards to multicollinearity of the variables utilized in this study. That is, although the measures claim to be measuring two different constructs, attachment and responsiveness do not act differently statistically.