Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey : Various Segmentation Approaches to Iris Recognition

Biometrics refers to the authentication of an individual’s identity based on his physical or behavioral traits. The iris, one of the biometrics stands out among other biometric techniques because of its unique features like stability and accuracy, segmentation of iris has its own major applications in the field of surveillance, forensics as well as in security purposes. The performance of the iris recognition systems depends heavily on segmentation and normalization techniques. A review of various segmentation approaches used in iris recognition is done in this paper.
Magnetic Induction Tomography

Magnetic induction tomography (MIT) is a low resolution imaging modality and attempts to reconstruct the interior conductivity distribution of the body. In MIT, the transmitter coils induce eddy currents in the body and the response field caused by the conductivity perturbations is sensed by an array of receiver coils. All the applications that were offered for electrical impedance tomography (EIT) are also a potential application for MIT. However, unlike EIT, MIT can look better through insulating tissues, e.g. ribcage which is made of bone tissue, and since the method is contactless, it does not suffer from the poor electrode contact. In this paper, the feasibility of lung imaging was investigated using a realistic thorax model of which the tissue boundaries were segmented from MRI images. The images were reconstructed from different simulated datasets, i.e. static, temporal and spectral datasets, to cover all the potential imaging approaches that MIT can offer. It was shown that the lung imaging is a feasible application for MIT, however, still some software and hard-ware improvements are essential before a clinical usage.
Approach for a joint global registration agency for research data

The scientific and information communities have largely mastered the presentation of, and linkages between, text-based electronic information by assigning persistent identifiers to give scientific literature unique identities and accessibility. Knowledge, as published through scientific literature, is often the last step in a process originating from scientific research data. Today scientists are using simulation, observational, and experimentation techniques that yield massive quantities of research data. These data are analyzed, synthesized, interpreted, and the outcome of this process is generally published as a scientific article. Access to the original data as the foundation of knowledge has become an important issue throughout the world and different projects have started to find solutions. Global collaboration and scientific advances could be accelerated through broader access to scientific research data. In other words, data access could be revolutionized through the same technologies used to make textual literature accessible. The most obvious opportunity to broaden visibility of and access to research data is to integrate its access into the medium where it is most often cited: electronic textual information. Besides this opportunity, it is important, irrespective of where they are cited, for research data to have an internet identity. Since 2005, the German National Library of Science and Technology (TIB) has offered a successful Digital Object Identifier (DOI) registration service for persistent identification of research data. In this white paper we discuss the possibilities to open this registration to a global consortium of information institutes and libraries.
Phase transition in a foreign exchange market-analysis based on an artificial market approach

In this study, we propose an artificial market approach, which is a new agent-based approach to foreign exchange market studies. Using this approach, emergent phenomena of markets such as the peaked and fat-tailed distribution of rate changes were explained. First, we collected the field data through interviews and questionnaires with dealers and found that the features of dealer interaction in learning were similar to the features of genetic operations in biology. Second, we constructed an artificial market model using a genetic algorithm. Our model was a multiagent system with agents having internal representations about market situations. Finally, we carried out computer simulations with our model using the actual data series of economic fundamentals and political news. We then identified three emergent phenomena of the market. As a result, we concluded that these emergent phenomena could be explained by the phase transition of forecast variety, which is due to the interaction of agent forecasts and the demand-supply balance. In addition, the results of simulation were compared with the field data. The field data supported the simulation results. This approach therefore integrates fieldwork and a multiagent model, and provides a quantitative explanation of micro-macro relations in markets.
A genetic algorithm to enhance transmembrane helices prediction

A transmembrane helix (TMH) topology prediction is becoming a central problem in bioinformatics because the structure of TM proteins is difficult to determine by experimental means. Therefore, methods which could predict the TMHs topologies computationally are highly desired. In this paper we introduce TMHindex, a method for detecting TMH segments solely by the amino acid sequence information. Each amino acid in a protein sequence is represented by a Compositional Index deduced from a combination of the difference in amino acid appearances in TMH and non-TMH segments in training protein sequences and the amino acid composition information. Furthermore, genetic algorithm was employed to find the optimal threshold value to separate TMH segments from non-TMH segments. The method successfully predicted 376 out of the 378 TMH segments in 70 testing protein sequences. The level of accuracy achieved using TMHindex in comparison to recent methods for predicting the topology of TM proteins is a strong argument in favor of our method.
Space Exploration Illuminates the Next Frontier for Teams Research

Effective teamwork is beneficial for organizations on Earth, but is a sine qua non for teams venturing into outer space. The prospect of sending a team to Mars by the year 2030 invites organizational scientists to take stock of what we know and what we still need to know about teams. The team endeavoring to Mars will be multicultural and interdisciplinary, living and working in uncomfortable and dangerous conditions, and doing so in close collaboration with distant teams back on Earth. Tackling the teamwork challenges associated with a mission to Mars present an opportunity to rapidly accelerate the science of teams. In this conceptual review, we explore seven complexities of teams that are both important and understudied. Results of structured interviews with experts on human space exploration regarding the nature of teamwork in long-duration space exploration illuminate seven complexities, or key features of teams, in general, that serve as a catalyst for identifying, informing, and motivating future directions of inquiry about teams. These features, and the research they inspire, may enable organizations to build more effective teams on Earth and beyond.
Intrinsically motivated classrooms a perspective for teachers

Implementation of Intrinsically Motivated Classrooms: A Guidebook for Teachers Students who are intrinsically motivated are more successful than students who are reliant on extrinsic motivators. Educators are in many ways responsible for the success of their students. It is the responsibility of the teacher to create an environment where students are motivated to learn. This work contains a guidebook focused on how educators can create a classroom environment where students are intrinsically motivated. Teachers can use this guidebook as a tool in their classroom. It provides specific as well as general strategies that can be implemented in elementary through high school classrooms to create an environment where students are intrinsically motivated to learn.
Design of Disturbance Observer via the Robust Stabilization and H∞ Loop Shaping Methods

Abstract The Disturbance observer (DOB) method is known to be effective in enhancing the performance of dynamic systems in the presence of disturbances. DOBs of various structures have been proposed to improve systems’ sensitivity functions for better disturbance rejection performance and robustness. However, the improvement to the sensitivity function may deteriorate robustness and transient responses. In this paper, we propose a new systematic method of designing the DOB. This method is based on the robust stabilization of the normalized coprime factor plant description and H ∞ loop shaping method. In our method, good system robustness can be achieved by Nehari stability margin, and the design parameters of the Q-filter for system robustness and performance can be determined systematically using a target loop transfer function. We applied this method to a MEMS stage. Simulation results show that the disturbance effect of the stage is reduced, and a robust system is achieved in the presence of parameter uncertainties.
Ethics by Design : A Conceptual Approach to Personal and Service Robot Systems

design of robots is driven largely by application area. Industrial robots have no need to be lightweight, soft or compliant, and, being inherently unsafe to humans, they are kept physically out of reach of factory workers. This approach is not tenable for personal and service robots, since, in addition to having an informational interface, people will expect human-robot interaction to be familiar and as safe as daily human-human interaction. This position paper describes how approaching both the software design and hardware design to mimic human attributes in behavior, physical aspects and motion quality will embed ethics in a deep and fundamental fashion, very different from artificially constructing a control scheme on top of an intrinsically human-unsafe structure.
The Square Root of NOT

Digital computers are built out of circuits that have definite, discrete states: on or off, zero or one, high voltage or low voltage. Engineers go to great lengths to make sure these circuits never settle into some intermediate condition. Quantum-mechanical systems, as it happens, offer a guarantee of discreteness without any engineering effort at all. When you measure the spin orientation of an electron, for example, it is always either "up" or "down," never in between. Likewise an atom gains or loses energy by making a "quantum jump" between specific energy states, without passing through intermediate energy levels. So why not build a digital computer out of quantum-mechanical devices, letting particle spins or the energy levels of atoms stand for binary units of information?
Long-term effects of the RealFit intervention on self-esteem and food craving

ABSTRACT Background: RealFit is a 13-week weight-reduction programme for adolescents. This study investigated the programme’s long-term effectiveness regarding the psychological outcomes of self-esteem and food craving. Methods: The study had a quasi-experimental design. Body mass index, self-esteem and food craving were assessed at baseline (T0), immediately after RealFit (T1), and after five months (T2) and one year (T3) of follow-up. Control participants (n = 32) were overweight adolescents who received no treatment. Results: Comparison between the intervention (n = 86) and control groups showed a significant difference for the self-esteem domain of global self-worth (1.63; 95% confidence interval: 0.28 to 2.99) in favour of the intervention group. The differences regarding overall self-esteem and the physical appearance domain showed a trend towards improvement. No significant difference was found for food craving. Conclusions: Taking all results and limitations into account, it may cautiously be concluded that RealFit has beneficial long-term effects on some domains of self-esteem, but no substantial effect on food craving. The appropriate duration and delivery of cue-exposure sessions in groups of overweight adolescents to decrease food craving should be investigated to further improve the RealFit intervention.
Cultivation of Chlorella vulgaris and Arthrospira platensis with Recovered Phosphorus from Wastewater by Means of Zeolite Sorption

In this study, zeolite was employed for the separation and recovery of P from synthetic wastewater and its use as phosphorus (P) source for the cultivation of the green microalga Chlorella vulgaris and the cyanobacterium Arthrospira (Spirulina) platensis. At P-loaded zeolite concentration of 0.15–1 g/L, in which P was limited, the two species displayed quite different behavior regarding their growth and biomass composition. C. vulgaris preferred to increase the intracellular P and did not synthesize biomass, while A. platensis synthesized biomass keeping the intracellular P as low as possible. In addition under P limitation, C. vulgaris did display some little alteration of the biomass composition, while A. platensis did it significantly, accumulating carbohydrates around 70% from about 15%–20% (control). Both species could desorb P from zeolite biologically. A. platensis could recover over 65% and C. vulgaris 25% of the P bounded onto zeolite. When P-loaded zeolite concentration increased to 5 g/L, P was adequate to support growth for both species. Especially in the case of C. vulgaris, growth was stimulated from the presence of P-loaded zeolite and produced more biomass compared to the control.
A constructive algorithm to determine the feasibility and weights of two-layer perceptrons for celled decision regions

Necessary and sufficient conditions for implementing particular decision regions by multi-layer perceptrons have been presented in recent studies. In this paper, from a viewpoint of engineering, a constructive algorithm is proposed to implement celled decision regions using two-layer perceptrons without any training procedure. The algorithm examines the feasibility of a celled decision region and then determines the weights of the second layer for a particular two-layer perceptron to implement the decision region if it is realizable. The algorithm is fast based on two aspects. First, it tests the feasibility and determines the weights without any training procedure. Second, the classifications of input patterns are based on integer manipulations since the weights determined by the algorithm are all integers. The proposed algorithm consists of only three simple steps and is implemented easily by computer programming languages.
Indiana Emergent Bilingual Student Time to Reclassification

In this study, we employed a discrete-time survival analysis model to examine Indiana emergent bilingual time to reclassification as fluent English proficient. The data consisted of five years of statewide English language proficiency scores. Indiana has a large and rapidly growing Spanish-speaking emergent bilingual population, and these students are prevalent in the low socioeconomic status group. Our findings suggest that Spanish home language status, low socioeconomic status, and special education status are negatively associated with the odds to reclassification. Based on our findings, we recommend a careful investigation to inform best practices that will meet the needs of Spanish-speaking emergent bilinguals and reduce inequities in education.
Geometry of multisymplectic Hamiltonian first order field theories

In the jet bundle description of field theories (multisymplectic models, in particular), there are several choices for the multimomentum bundle where the covariant Hamiltonian formalism takes place. As a consequence, several proposals for this formalism can be stated, and, on each one of them, the differentiable structures needed for setting the formalism are obtained in different ways. In this work we make an accurate study of some of these Hamiltonian formalisms, showing their equivalence. In particular, the geometrical structures (canonical or not) needed for the Hamiltonian formalism, are introduced and compared, and the derivation of Hamiltonian field equations from the corresponding variational principle is shown in detail. Furthermore, the Hamiltonian formalism of systems described by Lagrangians is performed, both for the hyper-regular and almost-regular cases. Finally, the role of connections in the construction of Hamiltonian field theories is clarified.
Interactive Scanning of Haptic Textures and Surface Compliance

In modern computer graphics, 3D scanning is common practise for the acquisition of the geometry of objects. However, in addition to geometric models, physical models of interaction behaviour are required for the realistic representation of objects in arbitrary environments. In this paper, we introduce a hand-held scanning approach for the acquisition of physical surface texture (roughness) of real- world 3D objects. Our system utilizes a low-cost mobile touch probe and image-based tracking to allow an operator to interactively scan a real-world object and generate estimates of surface texture and compliance. These scans can be integrated into the 3D scanning pipeline, just as colour imagery can be included into the pipeline for the acquisition of visual texture. We demonstrate that the acquired surface properties are of sufficient quality to allow for haptic display of the scanned object.
of the Annual Meeting of the Cognitive Science Society Title Evidence for Efficient Language Production in Chinese Permalink

Recent work proposes that language production is organized to facilitate efficient communication by means of transmitting information at a constant rate. However, evidence has almost exclusively come from English. We present new results from Mandarin Chinese supporting the hypothesis that Constant Entropy Rate is observed cross-linguistically, and may be a universal property of the language production system. We show that this result holds even if several important confounds that previous work failed to address are controlled for. Finally, we present evidence that Constant Entropy Rate is observed at the syllable level as well as the word level, suggesting findings do not depend on the chosen unit of observation.
Effects of ospemifene on the female reproductive and urinary tracts: translation from preclinical models into clinical evidence

ObjectiveTreatment of menopausal symptoms by compounds with tissue-selective estrogen agonist/antagonist effects, often called selective estrogen receptor modulators, has been researched as an alternative to the use of estrogen therapy. These structurally diverse molecules elicit tissue-dependent responses in hormone-responsive tissues and organs, exhibiting variations in estrogenic activity in preclinical models of postmenopausal reproductive tissues that may improve postmenopausal women’s health (eg, prevention and treatment of breast cancer, osteoporosis, and vulvar and vaginal atrophy). MethodsThis literature review investigates whether preclinical data predicted the clinical effects of ospemifene on female reproductive and urinary tract tissues and compares these findings with the specific vaginal effects of other estrogen receptor agonists/antagonists (tamoxifen, raloxifene, and bazedoxifene) in preclinical and clinical studies. Lasofoxifene, although not currently available, is included because of its unique effects on vaginal tissue. ResultsThe response of endometrial and vaginal tissues to estrogen receptor agonists/antagonists can be differentiated using transvaginal ultrasound, endometrial histopathology, cytologic examination of vaginal smears, assessment of physical changes in the vagina, and relief of symptoms associated with vulvar and vaginal atrophy (such as dyspareunia). ConclusionsAvailable evidence indicates that ospemifene has unique effects on tissue, leading to a favorable long-term profile for the relief of vulvar and vaginal atrophy compared with other estrogen receptor agonists/antagonists (eg, tamoxifen, raloxifene, and bazedoxifene) with no short-term concerns about endometrial safety (based on endometrial hyperplasia, carcinoma, endometrial spotting, and endometrial bleeding).
First results of hormone receptors' status in Malagasy women with invasive breast cancer

Introduction Breast cancer is the most common malignancy tumor amongst Malagasy women registered at the pathology unit of the “Institut Pasteur de Madagascar”. In Madagascar, there is no laboratory practicing hormone receptors' status on these tumors. Until now no study about hormone receptors' status of Malagasy women with invasive breast cancer was performed. So it will be the first study talking about this topic. The aim of this study was to determine hormone receptors' status in Malagasy women with invasive breast cancer. Methods This retrospective and descriptive study was based on patients' medical files from 2009 to 2011. It included all invasive breast cancer diagnosed in Malagasy women at the pathology laboratory located at the “Institut Pasteur de Madagascar”, in Antananarivo. Along this period this laboratory has sent paraffin blocks of invasive breast carcinoma in two pathological laboratories in France. Results We collected 77 cases of invasive breast cancer along this period. The mean age was 48.8 +/- 10.7, ranging from 26 years to 70 years. There were 46.8 % (n = 36) women with progesterone receptor positive (PR+), 53.2 % (n = 41) with progesterone receptor negative (PR-). For the estrogen receptor, 61.0 % (n = 47) were positive and 36.4 % (n = 28) were negative. ER+/PR+ represented 44.2 % (n = 34); ER-/PR- 33.8 % (n = 26); ER +/ PR- 16.8 % (n = 13); ER-/PR+ and ER-/PR- represented respectively 2.6 % (n = 2). Conclusion Patients in our study had more important rate of ER-, PR- and a less important rate of ER+/PR+, PR+. These results suggest that more study related to Hormone Receptor profile should be conducted in Malagasy women with breast cancer.
Tuition Rich, Mission Poor: Nonresident Enrollment Growth and the Socioeconomic and Racial Composition of Public Research Universities

Many public research universities fail to enroll a critical mass of low-income and underrepresented minority (URM) students. Though founded with a commitment to access, public research universities face pressure to increase tuition revenue and to recruit high-achieving students. These pressures create an incentive to recruit nonresident students, who tend to pay more tuition and score higher on admissions exams, but who also tend to be richer and are less likely be Black or Latino. This paper examines whether the growing share of nonresident students was associated with a declining share of low-income and URM students at public research universities. Institution-level panel models revealed that growth in the proportion of nonresident students was associated with a decline in the proportion of low-income students. This negative relationship was stronger at prestigious universities and at universities in high-poverty states. Growth in the proportion of nonresident students was also associated with a decline in the proportion of URM students. This negative relationship was stronger at prestigious universities, universities in states with large minority populations, and universities in states with affirmative action bans. These findings yield insights about the changing character of public research universities and have implications for the campus climate experienced by low-income and URM students.