Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Diversity of Echinococcus granulosus in Center of Iran

Hydatid cyst caused by Echinococcus granulosus is one of the most important parasitic diseases around the world and many countries in Asia, including Iran, are involved with this infection. This disease can cause high mortality in humans as well as economic losses in livestock. To date, several molecular methods have been used to determine the genetic diversity of E. granulosus. So far, identification of E. granulosus using real-time PCR fluorescence-based quantitative assays has not been studied worldwide, also in Iran. Therefore, the aim of this study was to investigate the genetic diversity of E. granulosus from center of Iran using real-time PCR method. A total of 71 hydatid cysts were collected from infected sheep, goat, and cattle slaughtered in Isfahan, Iran during 2013. DNA was extracted from protoscolices and/or germinal layers from each individual cyst and used as template to amplify the mitochondrial cytochrome c oxidase subunit 1 gene (cox1) (420 bp). Five cattle isolates out of 71 isolates were sterile and excluded from further investigation. Overall, of 66 isolates, partial sequences of the cox1 gene of E. granulosus indicated the presence of genotypes G1 in 49 isolates (74.2%), G3 in 15 isolates (22.7%), and G6 in 2 isolates (3.0%) in infected intermediate hosts. Sixteen sequences of G1 genotype had microgenetic variants, and they were compared to the original sequence of cox1. However, isolates identified as G3 and G6 genotypes were completely consistent with original sequences. G1 genotype in livestock was the dominant genotype in Isfahan region, Iran.
Critical Thinking inside College Classrooms: Evidence from Four Institutional Case Studies. ASHE Annual Meeting Paper.

This comparative case study investigated instructional methods that effectively enhance the development of students' critical thinking. Four institutions were selected for study; two at which students reported experiencing high degrees of growth in the ability to think critically, and two at which students reported experiencing low degrees of growth. Analysis of the data, which came primarily from 55 interviews and 28 classroom observations, suggests that the development of critical thinking is linked to an emphasis on writing and rewriting. At the two schools scoring high on an institutional growth in critical thinking (IGCT) measure, there was a strong focus on writing, a focus absent from the two schools that scored low on IGCT. At one school (high IGCT, low selectivity) a curricular policy stipulates that writing be an integral part of all course programs (which are taught by a multi-disciplinary team of faculty members). Another classroom factor that appears related to the development of critical thinking is an emphasis on class discussion, which again exists at the two high IGCT institutions. Appendices include a table showing selection criterion for case study sites, a summary of classroom observation data, and descriptions of categories for the observation data. (Contains 38 references.) (RH) Reproductions supplied by EDRS are the best that can be made from the original document. Critical Thinking Inside College Classrooms: Evidence from Four Institutional Case Studies
Resolution vs. tracking error: zoom as a gain controller

During tracking, lens zoom acts as a gain between scene dynamics and fixation errors, providing a trade-off between maximizing resolution and minimizing tracking error. Using a linear Kalman filter model, it is shown that when image measurement error scales with focal length, the filter is invariant to zoom. When the error is of fixed size, however, zooming alters the balance between process and measurement errors in a counter-intuitive manner. It is shown that this balance can be restored by appropriate adjustment of the process noise. With a zoom invariant filter, zoom can be used to ensure that fixation errors remain bounded. To this end, an error variance control method is proposed which gives high confidence that the target will not leave the image during tracking. To implement such a scheme, equipment delays and responses must be known, including those of the zoom lenses. Experiments to measure these are described, and overall results are presented for 30 Hz tracking of real scenes.
Intraventricular Administration of rt-PA in Patients with Intraventricular Hemorrhage

Objective: Intraventricular hemorrhage (IVH) represents a clinicopathologic entity with a dismal prognosis. The associated mortality rate has been reported as high as 80%; the morbidity is also quite high. The use of various fibrinolytic agents (streptokinase, urokinase, and recombinant tissue-type plasminogen activator [rt-PA]) has been reported in a small number of clinical series with a very limited number of participants, yielding significant variability regarding inclusion criteria, treatment protocol, and outcome analysis. Methods: In our prospective study, we report our experience using rt-PA in 21 patients with IVH. Patients with IVH of aneurysmal or arteriovenous malformation origin were excluded. Intraventricular administration of rt-PA was initiated within 24 hours after the ictal event (dose, 3 mg every 24 hours) through a ventricular catheter. The patients’ intracranial and cerebral perfusion pressures, cerebrospinal fluid (CSF) cell count, and head CT scans with emphasis to frontal horn dimension and inner cranium diameter at the same level ratio were collected and analyzed. Results: Good outcome was observed in 47.5% of our patients, whereas 28.5% died and 24.0% survived with severe disability. The development of rt-PA–associated complications was as follows: new hemorrhage in 19%, infection in 14.3%, and CSF pleocytosis in 100% of patients. Permanent CSF shunt was required in 40%. The intermediate (3-month) follow up of our survivors showed no significant outcome changes compared with the immediate (1-month) follow up. Conclusions: Intraventricular administration of rt-PA appears to be beneficial in cases of IVH even though it is occasionally associated with serious complications. Further multi-institutional studies are required for validating this treatment modality and standardizing its parameters.
A Dynamic $p$ -Adaptive DGTD Algorithm for Electromagnetic and Multiphysics Simulations

In the time-domain simulation of electromagnetic and multiphysics problems, the distributions of physical quantities of interest vary in both space and time. To achieve a good spatial resolution, high-order basis functions can be used to expand the unknown quantities, which is known as the <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-refinement. However, a global and static <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-refinement will increase the computational cost significantly. In this paper, a dynamic <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-adaptation algorithm is proposed based on the discontinuous Galerkin time-domain method, which is able to determine and adjust the basis order in a given discretization element in real time of the simulation. Based on the relation between the nodal and modal approximations defined on unstructured tetrahedral elements, an error estimator, which is very cheap to compute, is developed to determine the proper basis order to achieve a desired numerical accuracy. The dynamic <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-adaptation algorithm proposed in this paper is able to capture the fast varying physics by changing the order of basis functions <italic>wherever</italic> and <italic>whenever</italic> needed. Several numerical examples adopted from multiple physical disciplines are presented to demonstrate the accuracy, efficiency, and flexibility of the proposed algorithm in the simulation of electromagnetic and multiphysics problems.
Closed-Loop Inverse Kinematics Schemes for Constrained Redundant Manipulators with Task Space Augmentation and Task Priority Strategy

This article presents new closed-loop schemes for solving the inverse kinematics of constrained redundant manipula tors. In order to exploit the space of redundancy, the end- effector task is suitably augmented by adding a constraint task. The success of the technique is guaranteed either by specifying the constraint task ad hoc or by resorting to a task priority strategy. Instead of previous inverse kinemat ics schemes that use the Jacobian pseudoinverse, the schemes in this work are shown to converge using the Jacobian transpose. A number of case studies illustrate different ways of solving redundancy in the context of the proposed schemes.
Data clustering-based anomaly detection in industrial control systems

Modern Networked Critical Infrastructures (NCI), involving cyber and physical systems, are exposed to intelligent cyber attacks targeting the stable operation of these systems. In order to ensure anomaly awareness, the observed data can be used in accordance with data mining techniques to develop Intrusion Detection Systems (IDS) or Anomaly Detection Systems (ADS). There is an increase in the volume of sensor data generated by both cyber and physical sensors, so there is a need to apply Big Data technologies for real-time analysis of large data sets. In this paper, we propose a clustering based approach for detecting cyber attacks that cause anomalies in NCI. Various clustering techniques are explored to choose the most suitable for clustering the time-series data features, thus classifying the states and potential cyber attacks to the physical system. The Hadoop implementation of MapReduce paradigm is used to provide a suitable processing environment for large datasets. A case study on a NCI consisting of multiple gas compressor stations is presented.
User-provided networking for QoE provisioning in mobile networks

With the accelerating pace of development in mobile networks, mobile network operators and service providers are facing new challenges, especially in terms of quality of experience provisioning. To address these challenges, we present a new network paradigm by taking advantage of an emerging type of user-provided network. In particular, the proposed scheme allows end users to play a crucial role in both QoE evaluation and network improvement. Some points for possible challenges and future research are given. Also, a case study with the proposed resource scheduling algorithm is conducted to illustrate the win-win situation created by the proposed network paradigm.
Edge sets: an effective evolutionary coding of spanning trees

The fundamental design choices in an evolutionary algorithm (EA) are its representation of candidate solutions and the operators that will act on that representation. We propose representing spanning trees in EAs for network design problems directly as sets of their edges and we describe initialization, recombination, and mutation operators for this representation. The operators offer locality, heritability, and computational efficiency. Initialization and recombination depend on an underlying random spanning-tree algorithm. Three choices for this algorithm, based on the minimum spanning-tree algorithms of Prim and Kruskal and on random walks, respectively, are examined analytically and empirically. We demonstrate the usefulness of the edge-set encoding in an EA for the NP-hard degree-constrained minimum spanning-tree problem. The algorithm's operators are easily extended to generate only feasible spanning trees and to incorporate local, problem-specific heuristics. Comparisons of this algorithm to others that encode candidate spanning trees via the Blob Code, with network random keys, and as strings of weights indicate the superiority of the edge-set encoding, particularly on larger instances.
Experimental comparison of MPPT methods for PV systems under dynamic partial shading conditions

Solar energy is one of the most popular kinds of renewable energy sources. The efficiency of the photovoltaic (PV) system depends on many factors. One of them is the maximum power point tracker (MPPT) method implemented in the control unit. In practice, PV generators are often partially shaded or dynamically shaded by many kinds of objects. In these conditions it is difficult to find the maximum power point (MPP) on the P-V curve because of many local maxima, and the MPPT method performance may decrease. This paper presents a comparative study on seven commonly used MPPT methods under dynamic partial shading conditions. The experimental system was designed using a boost DC-DC converter, a monocrystalline PV module, a dsPIC-based control unit and a motorized linear guide. The results of the outdoor tests show that the Perturb and Observe (P&O) method have the best performances under dynamic partial shading conditions.
Pacific Asia Conference on Information Systems ( PACIS ) 2015 A Method for the Design of Gamified Trainings

The use of game elements in non-game contexts (gamification) -has previously been widely explored in contexts such as healthcare and marketing but less extensively in education and training. In this paper we explore the use of gamification in education and training. Traditional training methods often fail to engage or motivate students, especially Digital Natives raised from a young age with apps and games. This paper explores how classor computer-based trainings can be (re)designed using gamification to increase student engagement and motivation. The paper first develops a taxonomy of game elements, based on a literature review. It then provides an Educational Game Element Database (EGEDB) that includes the taxonomy and that represents the effect of each game element on learning. Following a Design Science Research approach, the paper proposes a method for the design of ‘’gamified’’ training. The method extends the instructional design model ADDIE (Analyze, Design, Develop, Implement, Evaluate) and uses the EGEDB to select game elements. We evaluate the method using a case study of gamified training design for a customer service contact team at Dutch Railways. The resulting gamified training design is evaluated by trainers from the same company.
Characterization of a Self-sufficient Trans-Anethole Oxygenase from Pseudomonas putida JYR-1

A novel flavoprotein monooxygenase, trans-anethole oxygenase (TAO), from Pseudomonas putida JYR-1, which is capable of catalyzing the oxidation of trans-anethole to p-anisaldehyde, was heterologously expressed in E. coli and purified. Enzymatic kinetics of diverse substrates and cofactors revealed that TAO is likely to be a novel self-sufficient flavoprotein monooxygenase. Enzyme assays of GST-TAO demonstrated that TAO catalyzed a trans-anethole oxidation reaction without auxiliary component enzyme-like electron-transfer flavin reductases. The single component TAO had the ability to reduce flavin cofactors and simultaneously oxidize trans-anthole to p-anisaldehyde. In the processes of reduction of flavin and oxidation of trans-anethole, TAO accepted various flavin and NAD(P)H cofactors. TAO also catalyzed oxidation of isoeugenol, O-methyl isoeugenol, and isosafrole, all of which contain the 2-propenyl functional group on the aromatic ring structure with different catalytic efficiency. TAO had the greatest catalytic efficiency (k cat/K m) with the original substrate, trans-anethole. Investigation about partially deleted mutants of TAO indicated that reductase active sites appeared to be located near the N terminal. Site directed mutagenesis studies also proved that the proposed flavin binding sites, Trp-38, Thr-43, Tyr-55, were critical for flavin reduction. However, disruption of any portion of TAO eliminated the oxygenase activity.
Dopamine D1‐like receptor antagonism in amygdala impairs the acquisition of glucose‐conditioned flavor preference in rats

This study examined the role of dopamine within the amygdala (AMY) in flavor preference learning induced by post‐oral glucose. In Experiment 1, rats were trained with a flavor [conditioned stimulus (CS+)] paired with intragastric (IG) infusions of 8% glucose and a different flavor (CS−) paired with IG water infusions. The CS+ preference was evaluated in two‐bottle tests following bilateral injection of the dopamine D1‐like receptor antagonist, SCH23390 (SCH), into the AMY at total doses of 0, 12, 24 and 48 nmol. SCH produced dose‐dependent reductions in CS+ intake but did not block the CS+ preference except at the two highest doses, which also greatly suppressed the CS intakes. In Experiment 2, new rats were injected daily in the AMY with either saline or SCH (12 nmol), prior to training sessions with CS+/IG glucose and CS−/IG water. In the two‐bottle tests, SCH rats, unlike the control rats, failed to prefer the CS+ (55 vs. 81%). In Experiments 3 and 4, new rats were trained as in Experiment 2, except that brain injections were in the basolateral and central nuclei of the AMY, respectively. SCH rats learned to prefer the CS+ to the CS−, although their preference was weaker than that displayed by the control rats (Experiment 3: 59 vs. 80%; Experiment 4: 73 vs. 88%). These results show an essential role for D1‐like receptor activation in the AMY in the acquisition of flavor preference learning induced by the post‐oral reinforcing properties of glucose. A distributed network mediating flavor–nutrient incentive learning is discussed.
Proteomics of Aggregatibacter actinomycetemcomitans Outer Membrane Vesicles

Aggregatibacter actinomycetemcomitans is an oral and systemic pathogen associated with aggressive forms of periodontitis and with endocarditis. Outer membrane vesicles (OMVs) released by this species have been demonstrated to deliver effector proteins such as cytolethal distending toxin (CDT) and leukotoxin (LtxA) into human host cells and to act as triggers of innate immunity upon carriage of NOD1- and NOD2-active pathogen-associated molecular patterns (PAMPs). To improve our understanding of the pathogenicity-associated functions that A. actinomycetemcomitans exports via OMVs, we studied the proteome of density gradient-purified OMVs from a rough-colony type clinical isolate, strain 173 (serotype e) using liquid chromatography-tandem mass spectrometry (LC-MS/MS). This analysis yielded the identification of 151 proteins, which were found in at least three out of four independent experiments. Data are available via ProteomeXchange with identifier PXD002509. Through this study, we not only confirmed the vesicle-associated release of LtxA, and the presence of proteins, which are known to act as immunoreactive antigens in the human host, but we also identified numerous additional putative virulence-related proteins in the A. actinomycetemcomitans OMV proteome. The known and putative functions of these proteins include immune evasion, drug targeting, and iron/nutrient acquisition. In summary, our findings are consistent with an OMV-associated proteome that exhibits several offensive and defensive functions, and they provide a comprehensive basis to further disclose roles of A. actinomycetemcomitans OMVs in periodontal and systemic disease.
Predicting Novel Features of Toll-Like Receptor 3 Signaling in Macrophages

The Toll-like receptor (TLR) 3 plays a critical role in mammalian innate immune response against viral attacks by recognizing double-stranded RNA (dsRNA) or its synthetic analog polyinosinic-polycytidylic acid (poly (I∶C)). This leads to the activation of MAP kinases and NF-κB which results in the induction of type I interferons and proinflammatory cytokines to combat the viral infection. To understand the complex interplay of the various intracellular signaling molecules in the regulation of NF-κB and MAP kinases, we developed a computational TLR3 model based upon perturbation-response approach. We curated literature and databases to determine the TLR3 signaling topology specifically for murine macrophages. For initial model creation, we used wildtype temporal activation profiles of MAP kinases and NF-κB and, for model testing, used TRAF6 KO and TRADD KO data. From dynamic simulations we predict i) the existence of missing intermediary steps between extracellular poly (I∶C) stimulation and intracellular TLR3 binding, and ii) the presence of a novel pathway which is essential for JNK and p38, but not NF-κB, activation. Our work shows activation dynamics of signaling molecules can be used in conjunction with perturbation-response models to decipher novel signaling features of complicated immune pathways.
Hemoglobin Expression in Nonerythroid Cells: Novel or Ubiquitous?

Hemoglobin (Hb) is a major protein involved in transport of oxygen (O2). Red blood cells (RBCs) contain maximum amount of Hb and because of their unique structure and plasticity they transport O2 to various tissues of the body at an optimal concentration. Recently, it has been reported that, apart from RBCs, Hb is also expressed by nonerythroid cells such as epithelial cells of different origin. The cells expressing Hb are from the tissues where maintenance of O2 homeostasis is of paramount importance. Hb expression has been observed in the epithelial cells from human tissues including lungs, neurons, retina, and endometrium. Our group has recently demonstrated that Hb is expressed by the cervicovaginal epithelial cells. We further showed that, apart from maintaining O2 homeostasis, Hb and the peptides derived from it play an indispensable role in the protection of vaginal epithelium by exhibiting antimicrobial activity. In this review, we discuss the significance of Hb expression in vaginal epithelial cells and its role in the recognition of pathogens thereby reducing the risk and/or severity of inflammation and/or infections and the possible mechanism by which Hb exhibits antimicrobial and antioxidative functions.
Augmented Lagrangian methods for variational inequality problems

We introduce augmented Lagrangian methods for solving finite dimensional variational inequality problems whose feasible sets are defined by convex inequalities, generalizing the proximal augmented Lagrangian method for constrained optimization. At each iteration, primal variables are updated by solving an unconstrained variational inequality problem, and then dual variables are updated through a closed formula. A full convergence analysis is provided, allowing for inexact solution of the subproblems.
Flow computations on imprecise terrains

We study water flow computation on imprecise terrains. We consider two approaches to modeling flow on a terrain: one where water flows across the surface of a polyhedral terrain in the direction of steepest descent, and one where water only flows along the edges of a predefined graph, for example a grid or a triangulation. In both cases each vertex has an imprecise elevation, given by an interval of possible values, while its (x, y)-coordinates are fixed. For the first model, we show that the problem of deciding whether one vertex may be contained in the watershed of another is NP-hard. In contrast, for the second model we give a simple O(n log n) time algorithm to compute the minimal and the maximal watershed of a vertex, where n is the number of edges of the graph. On a grid model, we can compute the same in O(n) time.