Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecological and Morphological Profile of Floating Spherical Cladophora socialis Aggregations in Central Thailand

The unique beauty of spherical aggregation forming algae has attracted much attention from both the scientific and lay communities. Several aegagropilous seaweeds have been identified to date, including the plants of genus Cladophora and Chaetomorpha. However, this phenomenon remains poorly understood. In July 2013, a mass occurrence of spherical Cladophora aggregations was observed in a salt field reservoir in Central Thailand. The aims of the present study were to describe the habitat of the spherical aggregations and confirm the species. We performed a field survey, internal and external morphological observations, pyrenoid ultrastructure observations, and molecular sequence analysis. Floating spherical Cladophora aggregations (1–8 cm in diameter) were observed in an area ~560 m2, on the downwind side of the reservoir where there was water movement. Individual filaments in the aggregations were entangled in each other; consequently, branches growing in different directions were observed within a clump. We suggest that water movement and morphological characteristics promote the formation of spherical aggregations in this species. The molecular sequencing results revealed that the study species was highly homologous to both C. socialis and C. coelothrix. However, the diameter of the apical cells in the study species was less than that of C. coelothrix. The pyrenoid ultrastructure was more consistent with that of C. socialis. We conclude that the study species is C. socialis. This first record of spherical aggregations in this species advances our understanding of these formations. However, further detailed physical measurements are required to fully elucidate the mechanism behind these spherical formations.
Novel sensors for underground robotics

The end state of an autonomous system in South Africa's deep mines is a “fait accompli”. The current unacceptable safety records, and the increasing dangers as the mines get deeper, necessitate the removal of miners from the dangerous stope areas. Robotics seems an obvious solution. An autonomous robotic system to inspect the mine ceiling (hanging wall) is being developed at the Center for Mining Innovation as an initial robotic application for South African deep gold mines. A number of the key technologies needed to enable this are discussed. The localization system, the underground alternative to the GPS, is perhaps the single biggest hurdle needed in enabling underground robotics. A low cost, disposable solution for the small area gold stope (30m × 3m) is presented. Machine sensing of both the environment and of humans is critical in a shared working environment. Here we discuss alternatives to the current sensors used above ground for machine perception. In the deep gold mines the geothermal heat result in hot walls and thermal imaging becomes an option for structural imaging. The combination of temperature with a 3D data enables the determination of a risk measure, indicating potential danger areas. Potential methods of representing the risk data for the miner to interpret are discussed. Finally, the thermal camera in conjunction with a distance sensor is used to identify and track pedestrians in order to predict potential collisions.
Signal detection algorithms for two-dimensional intersymbol-interference channels

We develop several novel signal detection algorithms for two-dimensional intersymbol-interference channels. The core in all these schemes is a modified one-dimensional maximum aposteriori (MAP) detection algorithm that operates over single and multiple rows providing a balanced performance vs. complexity tradeoff. We explore 2-D iterative algorithms that operate by feeding extrinsic information from multi-row/column detectors in a turbo fashion. Multi-row/column MAP detection using 2-D turbo-processing yields more than 2 dB signal-to-noise ratio (SNR) gain compared to a non-iterative multi-row detector over the additive white Gaussian channel and within 0.1 dB of the ML estimate.
When Online Communities Collide: Boundary Identity Construction and Spanning

Online brand communities reflect a shared interest among participants that sustains community identity around and through brand consumption. While exchanges within such a community are typically supportive, conflict can exist between different, and sometimes competing, brand communities. The phenomena of communities in conflict introduces an element of ‘other’ that allows each community to delineate its values more succinctly by affording a comparative point of reference. The aim of this research is to understand online inter-community conflict using a boundary object theory lens to examine the how online brand communities construct and span boundaries. Using the example of two online brand communities comprising the followers of the authors J.K. Rowling and Terry Pratchett, preliminary results illuminate how discrete communities assert their individual boundary identity construction and spanning.
Certificate management using distributed trusted third parties

In this chapter, a novel way of delegating a TTP service from a central TTP to a secure execution environment (SEE) running on a user's machine is proposed. It also shows significant advantages for some types of TTP service and, in particular, it may be a useful technique for solving some of the problems traditionally associated with certificate authorities (CAs).
Gradient Pile up for Edge Detection on DSP

Edge detection is an important task on image processing. Many edge detectors algorithms have already been proposed, but most of them are based on step edges model and applying smooth filters to minimize the noise and the image derivative or gradient to enhance the edges. However, image sensors have a limited bandwidth, producing ramp edges with the same gradient magnitude as those produced by noise. This work presents a DSP implementation of the Gradient Pile up, an algorithm proposed to edge detection, enhancing the gradient correspondent to ramp edges without amplifying the noisy edges. The experimental results show that the proposed DSP implementation of the pile up process is efficient on enhancement of the gradient of an image and time required for its execution comparing with a PC implementation.
Private image computation: The case of cloud based privacy-preserving SIFT

In this paper, we present SecSIFT, a high-performance cloud based image feature detection system for performing Scalar Invariant Feature Transform (SIFT) over private image data without compromising the privacy. In contrast to previous works, we outsource the computation of image feature detection to a set of independent, co-operative cloud servers, and keep the outsourced computation procedures as simple as possible. Using this framework, we are not restricted by efficiency limitations of homomorphic encryption scheme and thus are able to implement applications such as social discovery or behavior prediction with less complexity on computation and communication.
Optimizing the Ant Colony Optimization Algorithm Using Neural Network for the Traveling Salesman Problem

Ant Colony Optimization (ACO) has been proved to be one of the most effective algorithms to solve a wide range of combinatorial optimization (or NP-hard) problems as the Travelling Salesman Problem (TSP). The first step of an ACO algorithm is setting the parameters that drive the algorithm. The basic parameters that are used in ACS algorithms are; number of ants, the relative importance (or weight) of pheromone, the relative importance of heuristics value, initial pheromone value, evaporation rate, and a parameter to control exploration or exploitation. Generally these parameters are set as discrete values, but past studies has shown that the behavior of the algorithm can be influenced by the modification of the parameters. In this paper, we propose a Neural Network (NN) to adapt two parameters of the ACO algorithm dynamically. The proposed hybrid algorithm is applied on the classical TSP, and tested on different TSP benchmark instances.
Implementation of the CORAL deductive database system

CORAL is a deductive database system that supports a rich declarative language, provides a wide range of evaluation methods, and allows a combination of declarative and imperative programming. The data can be persistent on disk or can reside in main-memory. We describe the architecture and implementation of CORAL. There were two important goals in the design of the CORAL architecture: (1) to integrate the different evaluation strategies in a reasonable fashion, and (2) to allow users to influence the optimization techniques used so as to exploit the full power of the CORAL implementation. A CORAL declarative program can be organized as a collection of interacting modules and this modular structure is the key to satisfying both these goals. The high level module interface allows modules with different evaluation techniques to interact in a transparent fashion. Further, users can optionally tailor the execution of a program by selecting from among a wide range of control choices at the level of each module. CORAL also has an interface with C++, and users can program in a combination of declarative CORAL, and C++ extended with CORAL primitives. A high degree of extensibility is provided by allowing C++ programmers to use the class structure of C++ to enhance the CORAL implementation.
THE MARGINALIZED PARTICLE FILTER - ANALYSIS, APPLICATIONS AND GENERALIZATIONS

The marginalized particle filter is a powerful combination of the particle filter and the Kalman filter, which can be used when the underlying model contains a linear sub-structure, subject to Gaussian noise. This paper outlines the marginalized particle filter and very briefly hint at pos- sible generalizations, giving rise to a larger family of marginalized nonlinear filters. Furthermore, we analyze several properties of the marginalized particle filter, including its ability to reduce variance and its computational complexity. Finally, we provide an introduction to various applications of the marginalized particle filter.
Rotationally Supported Virgo Cluster Dwarf Elliptical Galaxies: Stripped Dwarf Irregular Galaxies?

New observations of 16 dwarf elliptical galaxies (dEs) in the Virgo Cluster indicate that at least seven dEs have significant velocity gradients along their optical major axis, with typical rotation amplitudes of 20–30 km s-1. Of the remaining nine galaxies in this sample, six have velocity gradients of less than 20 km s-1 kpc-1, while the other three observations had too low a signal-to-noise ratio to determine an accurate velocity gradient. Typical velocity dispersions for these galaxies are ∼44 ± 5 km s-1, indicating that rotation can be a significant component of the stellar dynamics of Virgo dEs. When corrected for the limited spatial extent of the spectral data, the rotation amplitudes of the rotating dEs are comparable to those of similar-brightness dwarf irregular galaxies (dIs). Evidence of a relationship between the rotation amplitude and galaxy luminosity is found and, in fact, agrees well with the Tully-Fisher relation. The similarity in the scaling relations of dIs and dEs implies that it is unlikely that dEs evolve from significantly more luminous galaxies. These observations reaffirm the possibility that some cluster dEs may be formed when the neutral gaseous medium is stripped from dIs in the cluster environment. We hypothesize that several different mechanisms are involved in the creation of the overall population of dEs and that stripping of infalling dIs may be the dominant process in the creation of dEs in clusters like Virgo.
A new algorithm of counting the number of small stopping sets and girth in QC-LDPC Codes

It is well known that the performance of low-density parity check (LDPC) codes under iterative decoding is determined by certain combinatorial structures (such as stopping sets and girth) in the Tanner graph. The difficulty in enumerating all possible combinations of the columns may prevent an efficient search of good LDPC codes with small stopping sets and girth. To solve the problem, this paper presents a new algorithm of counting the number of small stopping sets and girth by analyzing the shapes of the cycles of Tanner graph in parity check matrix for designing good LDPC codes which is less complex than the existing algorithms. This method can be used effectively to evaluate the performance of LDPC codes according to their small stopping sets and girth distributions.
Impact of cannibalism on predator-prey dynamics: size-structured interactions and apparent mutualism.

Direct and indirect interactions between two prey species can strongly alter the dynamics of predator-prey systems. Most predators are cannibalistic, and as a consequence, even systems with only one predator and one prey include two prey types: conspecifics and heterospecifics. The effects of the complex direct and indirect interactions that emerge in such cannibalistic systems are still poorly understood. This study examined how the indirect interaction between conspecific and heterospecific prey affects cannibalism and predation rates and how the direct interactions between both species indirectly alter the effect of the cannibalistic predator. I tested for these effects using larvae of the stream salamanders Eurycea cirrigera (prey) and Pseudotriton ruber (cannibalistic predator) by manipulating the relative densities of the conspecific and heterospecific prey in the presence and absence of the predator in experimental streams. The rates of cannibalism and heterospecific predation were proportional to the respective densities and negatively correlated, indicating a positive indirect interaction between conspecific and heterospecific prey, similar to "apparent mutualism. " Direct interactions between prey species did not alter the effect of the predator. Although both types of prey showed a similar 30% reduction in night activity and switch in microhabitat use in response to the presence of the predator, cannibalism rates were three times higher than heterospecific predation rates irrespective of the relative densities of the two types of prey. Cumulative predation risks differed even more due to the 48% lower growth rate of conspecific prey. Detailed laboratory experiments suggest that the 3:1 difference in cannibalism and predation rate was due to the higher efficiency of heterospecific prey in escaping immediate attacks. However, no difference was observed when the predator was a closely related salamander species, Gyrinophilus porphyriticus, indicating that this difference is species specific. This demonstrates that cannibalism can result in the coupling of predator and prey mortality rates that strongly determines the dynamics of predator-prey systems.
The Relationship Between Attachment Styles, Emotion Regulation and Psychopathology Symptoms in Turkish and American Students

Two samples of university students, one from Turkey and the other from the USA, were compared on measures of attachment styles, difficulties in emotional regulation and self-reported symptoms of psychopathology. Results indicated that for both samples the level of anxiety in attachment and the lack of strategies in emotional regulation predicted several symptoms of psychopathology. Differences emerged in demographic predictors with parents’ educational level predicting many of the symptoms in the Turkish population while age was the major demographic predictor in the USA sample. The results suggest that attachment and emotional regulation are universal personality factors contributing to psychopathology across cultures. The collectivistic cultural framework of the Turkish sample showed greater significance to family factors in contrast to the individualistic cultural influences in the USA sample.
Autonomous monitoring of vulnerable habitats using a wireless sensor network

In the natural sciences, researchers use a variety of techniques that rely on extensive man-hours and can therefore be difficult to scale. This obviously limits questions that concern large spatial scales or that involve large numbers of animals. Here, we describe the design and deployment of a wireless sensor network that delivers high resolution sensor data while monitoring seabirds on a UK National Nature Reserve. We describe some of the problems encountered and the solutions we have used. In general, the network has successfully demonstrated its utility in a real world scenario and will be extended and enhanced for the coming field season.
Kathaa: A Visual Programming Framework for NLP Applications

In this paper, we present Kathaa 1 , an open source web based Visual Programming Framework for NLP applications. It supports design, execution and analysis of complex NLP systems by choosing and visually connecting NLP modules from an already available and easily extensible Module library. It models NLP systems as a Directed Acyclic Graph of optionally parallalized information ﬂow, and lets the user choose and use available modules in their NLP applications irrespective of their technical proﬁciency. Kathaa exposes a precise Module deﬁnition API to allow easy integration of external NLP components (along with their associated services as docker containers), it allows everyone to publish their services in a standardized format for everyone else to use it out of the box.
Stellar pulsations excited by a scattered mass

We compute the energy spectra of the gravitational signals emitted when a mass m0 is scattered by the gravitational field of a star of mass M >> m0. We show that, unlike black holes in similar processes, the quasi-normal modes of the star are excited, and that the amount of energy emitted in these modes depends on how close the exciting mass can get to the star.
Detecting computer and network misuse through the production-based expert system toolset (P-BEST)

The paper describes an expert system development toolset called the Production-Based Expert System Toolset (P-BEST) and how it is employed in the development of a modern generic signature analysis engine for computer and network misuse detection. For more than a decade, earlier versions of P-BEST have been used in intrusion detection research and in the development of some of the most well known intrusion detection systems, but this is the first time the principles and language of P-BEST are described to a wide audience. We present rule sets for detecting subversion methods against which there are few defenses-specifically, SYN flooding and buffer overruns-and provide performance measurements. Together, these examples and performance measurements indicate that P-BEST based expert systems are well suited for real time misuse detection in contemporary computing environments. In addition, the simplicity of the P-BEST language and its close integration with the C programming language makes it easy to use while still being very powerful and flexible.
Activating Transcription Factor 6 (ATF6) Sequence Polymorphisms in Type 2 Diabetes and Pre-Diabetic Traits

Activating transcription factor 6 (ATF6) is located within the region of linkage to type 2 diabetes on chromosome 1q21-q23 and is a key activator of the endoplasmic reticulum stress response. We evaluated 78 single nucleotide polymorphisms (SNPs) spanning >213 kb in 95 people, from which we selected 64 SNPs for evaluation in 191 Caucasian case subjects from Utah and between 165 and 188 control subjects. Six SNPs showed nominal associations with type 2 diabetes (P = 0.001–0.04), including the nonsynonymous SNP rs1058405 (M67V) in exon 3 and rs11579627 in the 3′ flanking region. Only rs1159627 remained significant on permutation testing. The associations were not replicated in 353 African-American case subjects and 182 control subjects, nor were ATF6 SNPs associated with altered insulin secretion or insulin sensitivity in nondiabetic Caucasian individuals. No association with type 2 diabetes was found in a subset of 44 SNPs in Caucasian (n = 2,099), Pima Indian (n = 293), and Chinese (n = 287) samples. Allelic expression imbalance was found in transformed lymphocyte cDNA for 3′ untranslated region variants, thus suggesting cis-acting regulatory variants. ATF6 does not appear to play a major role in type 2 diabetes, but further work is required to identify the cause of the allelic expression imbalance.
Radioiodine treatment for non-toxic goitre

There is no ideal treatment for benign multinodular goitre. Besides surgery, which is recommended for large goitres or when malignancy cannot be excluded, the non-surgical treatment options are levothyroxine therapy and radioiodine (131I) therapy. Conventional 131I therapy [without recombinant human thyroid-stimulating hormone (rhTSH)] has been used for more than a decade in symptomatic non-toxic multinodular goitre, and although it does lead to significant thyroid volume reduction, relatively high activities of radioiodine are needed because of a frequent finding of a low thyroid radioiodine uptake. rhTSH, even when used in very small doses in combination with 131I therapy, enhances the thyroid volume reduction at lower 131I activities by doubling the thyroid radioiodine uptake. However, before rhTSH stimulation can be routinely used by clinicians to optimise the 131I therapy in multinodular goitre, aspects of this association, such as the cost-benefit and optimum rhTSH dose and safety, will have to be sufficiently clarified.
Unconstrained state-space predictive controller for non-minimum phase MIMO systems

Non-minimum phase systems are known to be difficult to control especially when Generalize Predictive Control (GPC) based on statespace representation is considered. To solve this problem, an innovative synthesis method is proposed. It appeals: first, to estimate unmeasured states in order to stabilize the process with a state feedback; second, to decouple the system inputs and outputs in order to control separately the dynamics of the obtained subsystems closed loops. Some illustrative simulation results for a given system are presented and discussed. The proposed method makes possible to optimize separately the GPC parameters for each subsystem.
Cardiometabolic Health in Obese Adolescents Is Related to Length of Obesity Exposure: A Pilot Study.

CONTEXT Metabolically healthy obesity (MHO) is found in a subset of obese individuals. OBJECTIVE This study sought to examine possible determinants of MHO related to the length of exposure to obesity, lifestyle factors, and dietary intake in adolescent boys. DESIGN This was a cross-sectional Childhood Obesity Prevalence And Treatment study. Participants and Main Measures: Of 313 boys age 13.0-17.9 years with a body mass index (BMI) ≥ 97th percentile for age, two study cohorts were established based on two definitions of metabolically unhealthy obesity (MUO). Cohort 1 included 18 boys with at least three risk factors (hypertension, dyslipidemia, dysglycemia) who were matched for age, weight, height, and BMI with 18 boys with MHO. Cohort 2 included 35 boys with at least two risk factors who were compared with 31 boys with MHO. MHO was defined by the absence of cardiometabolic risk factors (excluding waist). Data on lifestyle factors and BMI growth trajectories were compared (MHO vs MUO). RESULTS Boys with MUO (Cohort 1) presented with an earlier onset (4.3 vs 9.1 y; P = .005) and a longer duration of obesity (11.2 vs 6.4 y; P = .003) compared with those with MHO in both group comparisons using different MUO definitions. We found an overall trend toward higher BMI z scores (significant from 3-7 y; P < .001) in metabolically unhealthy compared with their healthy counterparts (Cohort 1). Boys with MHO had higher carbohydrate intake (P < .001). No additional determinants of MHO were observed. CONCLUSIONS Increased cardiometabolic risk in boys is related to an earlier onset and a longer duration of obesity.