Miracle-dz/UniFAR-FTUs huggingface dataset:
Genomic imbalances in key ion channel genes and telomere shortening in sudden cardiac death victims

Sudden cardiac death (SCD) can be caused by a number of reasons. Previous works have identified the genetic causes, such as alterations in the DNA sequence, for many of these diseases. We hypothesize that some patients may show genomic imbalances and changes in the gene copy number leading to genetic instability. To clarify this, we analysed DNA samples from SCD victims using comparative genomic hybridization (CGH), a molecular cytogenetic technique that permits the genome-wide screening of chromosomal imbalances, and telomere length measurement. DNA derived from peripheral blood and heart tissue of 14 SCD cases and six apparently healthy control individuals were subjected to CGH analysis. Telomere length measurements were done by the Southern blotting method. Eight out of 14 SCD cases exhibited changes in DNA/gene copy number. CGH analysis showed variation in the gene copy number of some of the genes associated with potassium (KCNAB1, KCNH2, and KCNA4) and calcium (RyR2, ATP2A2) ions which are involved in maintaining the ionic balance of the heart. Alterations in TERC and TERT genes were also detected in SCD victims. In nine SCD victims shorter telomeres were detected. This might have resulted from excessive cellular proliferation and/or oxidative stress in these individuals. Copy number changes observed and telomere shortening detected in SCD cases would possibly explain at least some of the causes of SCD at early ages in humans. Identification of biomarkers of SCD is of great importance and thus the present study will facilitate the identification of some of the biomarkers.
Sparse identification of a predator-prey system from simulation data of a convection model

The use of low-dimensional dynamical systems as reduced models for plasma dynamics is useful as solving an initial value problem requires much less computational resources than fluid simulations. We utilize a data-driven modeling approach to identify a reduced model from simulation data of a convection problem. A convection model with a pressure source centered at the inner boundary models the edge dynamics of a magnetically confined plasma. The convection problem undergoes a sequence of bifurcations as the strength of the pressure source increases. The time evolution of the energies of the pressure profile, the turbulent flow, and the zonal flow capture the fundamental dynamic behavior of the full system. By applying the sparse identification of nonlinear dynamics (SINDy) method, we identify a predator-prey type dynamical system that approximates the underlying dynamics of the three energy state variables. A bifurcation analysis of the system reveals consistency between the bifurcation structures, observ.
Modeling Linkages between Climate Policy and Land Use: An Overview

Agriculture and forestry play an important role in emitting and storing greenhouse gases. For an efficient and cost-effective climate policy, it is therefore important to include land use, land-use change, and forestry (LULUCF) explicitly in economy-climate models. This article gives an overview and assessment of existing approaches to include LULUCF into partial and general equilibrium economy-climate models. For each class of models, we describe different examples, their treatment of land, and their potential for and applicability to policy analysis, as well as their shortcomings. We identify data requirements and conceptual problems, and provide suggestions for future research.
Australian Tropical Marine Micromolluscs: An Overwhelming Bias

Assessing the marine biodiversity of the tropics can be overwhelming, especially for the Mollusca, one of the largest marine phyla in the sea. With a diversity that can exceed macrofaunal richness in many groups, the micro/meiofaunal component is one of most overlooked biotas in surveys due to the time-consuming nature of collecting, sorting, and identifying this assemblage. We review trends in micromollusc research highlighting the Australian perspective that reveals a dwindling taxonomic effort through time and discuss pervasive obstacles of relevance to the taxonomy of micromolluscs globally. Since a high during the 1970s, followed by a smaller peak in 2000, in 2010 we observe a low in micromolluscan collection activity in Australia not seen since the 1930s. Although challenging, considered planning at each step of the species identification pathway can reduce barriers to micromolluscan research (e.g., role of types, dedicated sampling, integration of microscopy and genetic methods). We discuss new initiatives to trial these methods in Western Australia, an understudied region with high biodiversity, and highlight why micromolluscs are worth the effort. A number of important fields that would benefit from increased focus on this group (e.g., ecological gaps) are considered. The methods and strategies for resolving systematic problems in micromolluscan taxonomy are available, only the desire and support to reverse the decline in knowledge remains to be found.
Criterion for the Design of Low-Power Variable Stiffness Mechanisms

Designing robotic systems capable of low-power operation, inherent to their compliant actuation, has been elusive in practical application. In this paper, we propose a physical measure to mathematically define mechanical designs that are suitable to realize stiffness modulation with low power cost. Using this measure, we present a mathematical formulation of an ideal variable stiffness mechanism unaffected by the external load during its operation. We then analyze several existing mechanisms from the literature to relate design features with analytical conditions inherent to low power stiffness modulation in practical designs. Through this analysis, we identify an approximate practical realization of an ideal actuator capable of stiffness modulation with inherently low power cost. Similar to a number of existing efficient variable stiffness mechanisms, this mechanism is able to hold a given stiffness setting with zero input force under no external load. However, unlike many other previously designed mechanisms, it enables infinite range stiffness modulation using finite control forces. A practical variable stiffness mechanism that is capable of infinite range stiffness modulation using finite control forces leads to lower power cost and reduced energy consumption.
Transient Stability Analysis of an Islanded Microgrid under Variable Load

In this paper, we investigate some aspects related to microgrid (MG) stability. Due to different applications of MG, its structure and deployment topology vary depending upon the nature of application and operating modes (islanded or grid connected). So, the stability of MGs varies accordingly. This paper precisely explains the stability aspects (e.g., phase angle and power losses) of remotely located islanded MG having the capability to integrate distributed energy sources. Initially, the stability of three bus system is assessed under variable load and find some gaps related to stability as MG involves a high penetration of distributed energy sources. These gaps indicate that stability of a MG is not only in the control of generation/load but also in its coordination with other loads. After that, we implement the load coordination technique and analyze the stability against fixed and dynamic loads. For comprehensive analysis, four different cases are considered in which we vary load at different bus bars and check the performance. Lastly, we integrate the distributed energy source to islanded MG and perform the stability analysis. For validation purpose, extensive simulations of the proposed cases are conducted using Matlab. Simulation results depict that load coordination technique is more efficient regarding MG stability.
Multiple intelligences, judgment, and realization of value

In the theory of multiple intelligences, Howard Gardner proposes a scientific justification for a more pluralistic pedagogy, while denying that science can determine educational goals. Wearing an educator's hat, however, he favors a pathway in which students come ‘to understand the most fundamental questions of existence … familiarly, the true, the beautiful, and the good. ’ Yet Gardner claims to exclude the realm of values from an intrinsic role in any of the intelligences; furthermore, the intelligences have no role to play in respect to values. The best we can hope is that some people are able to yoke these ‘scientifically and epistemologically separate’ realms together. This dichotomy is detrimental to Gardner's educational goals. An integral conception, acknowledging both that normativity is essential for the operation of intelligence and that pursuit of values is itself an intelligent undertaking, would better support Gardner's educational vision with a more comprehensively pluralistic view of knowing.
Glycoarray Technologies: Deciphering Interactions from Proteins to Live Cell Responses

Microarray technologies inspired the development of carbohydrate arrays. Initially, carbohydrate array technology was hindered by the complex structures of glycans and their structural variability. The first designs of glycoarrays focused on the HTP (high throughput) study of protein–glycan binding events, and subsequently more in-depth kinetic analysis of carbohydrate–protein interactions. However, the applications have rapidly expanded and now achieve successful discrimination of selective interactions between carbohydrates and, not only proteins, but also viruses, bacteria and eukaryotic cells, and most recently even live cell responses to immobilized glycans. Combining array technology with other HTP technologies such as mass spectrometry is expected to allow even more accurate and sensitive analysis. This review provides a broad overview of established glycoarray technologies (with a special focus on glycosaminoglycan applications) and their emerging applications to the study of complex interactions between glycans and whole living cells.
Statistical algorithms in fault detection and prediction: Toward a healthier network

Very high reliability/availability at affordable cost requires a proactive approach to system faults and failures. This calls for sophisticated fault detection algorithms that ultimately could evolve into fault prediction strategies. This paper presents statistical algorithms — the Operational Fault Detection (OFD) class of algorithms — toward reaching these goals. OFD algorithms analyze system performance metrics to detect fault signatures. The concept behind OFD is to raise alarms for conditions that adversely impact customer revenue or system performance. Initial versions of OFD, deployed in the field, count meaningful events and raise alarms when a test statistic, based on the event counts, exceeds a predefined threshold. Setting the thresholds required human intervention. This is considered time consuming by our customers, even though the concepts of OFD have been well received. This paper suggests a new generation — the second-generation OFD — that is inherently adaptive and requires minimal human intervention. These new algorithms are designed to detect system performance degradations, paving the way to more mature fault prediction strategies. Detecting degradations is a precursor to fault predictions, as degradations are often early signatures of potentially catastrophic faults.
Computation, Memory and Bandwidth Efficient Distillation Codes to Mitigate DoS in Multicast

In this paper we address the problem of Denial of Service (DoS) mitigation in multicast environment. The contribution of the paper is twofold: first, we introduce an optimization (PMT) on the Merkle tree distillation codes by leveraging the implicit redundancy of a Merkle tree representation. Second, we devise a new algorithm(CECInA) for encoding/decoding that mitigates DoS attacks on the end user device and reduces the buffer size in case of DoS. In particular, according to the type of DoS attack, CECInA achieves either complexity or buffering savings. This attack mitigation capability is not a feature offered by state of the art algorithms. Furthermore CECInA is particularly efficient when used in conjunction with PMT. We derive and plot analytical results that indicates that the proposed solutions are effective. Hence, CECInA can be a viable solution to mitigate DoS in multicast, particularly suited for contexts in which end-user devices are resource constrained. As for PMT, note that it is a general technique that can be adopted independently from CECInA.
Adaptive Finite Element Simulation of Incompressible Flows by Hybrid Continuous-Discontinuous Galerkin Formulations

In this work we design hybrid continuous-discontinuous finite element spaces that permit discontinuities on nonmatching element interfaces of nonconforming meshes. Then we develop an equal-order stabilized finite element formulation for incompressible flows over these hybrid spaces, which combines the element interior stabilization of SUPG-type continuous Galerkin formulations and the jump stabilization of discontinuous Galerkin formulations. Optimal stability and convergence results are obtained. For the adaptive setting, we use a standard error estimator and marking strategy. Numerical experiments show the optimal accuracy of the hybrid algorithm for both uniformly and adaptively refined nonconforming meshes. The outcome of this work is a finite element formulation that can naturally be used on nonconforming meshes, as discontinuous Galerkin formulations, while keeping the much lower CPU cost of continuous Galerkin formulations.
Implementing education reform: EFL teachers’ perspectives

The National Education Act of 1999 in Thailand mandated a transition from teacher- to learner-centred instruction for all subjects including English. This shift was associated with the development of communicative ability in English to meet the needs of globalization. The current study investigated the policy behind and implementation of the reform in English teaching following Johnson's (1989) decision-making framework for a coherent curriculum. Several observations of English classes (grades 5–6) revealed no evidence of communicative language use. Stimulated recall and interviews with teachers revealed confusion about the reform's principles and their application. Teachers were concerned about their English proficiency, insufficient training, and inadequate resources and professional support. Of the four interviewed supervisors, one felt that the reform's principles were not suitable for teaching English. Findings point to areas of the curriculum in which coherence can be lost during reform.
Removal of C.I. Basic Yellow 2 from aqueous solution by low‐cost adsorbent: hardened paste of Portland cement

The adsorption of C.I. Basic Yellow 2 (BY2) from aqueous solutions on to hardened paste of Portland cement (HPPC) as a low‐cost adsorbent and its adsorption kinetics at different conditions were studied. The adsorption process was followed by an online spectrophotometric analysis system, which consisted of a UV‐Vis spectrophotometer, a designed spectrophotometric cell, a peristaltic pump and a glass reactor. The effect of experimental parameters, including initial dye concentration, mass of HPPC, initial pH and temperature, on adsorption was studied over a 30 min adsorption period. For the kinetic study, the obtained data were treated according to various kinetic models. The results revealed that the experimental data were better fitted to the first‐order kinetics model than to the second‐order and intraparticle diffusion models. Equilibrium isotherms for the adsorption of BY2 on HPPC were analysed by Freundlich and Langmuir isotherms equations using the linear correlation coefficient. The Freundlich isotherm gave the best correlation of adsorption.
Representation of Islam and Muslims in the Australian Media, 2001–20051

Abstract Muslim Australians believe that prevailing media attitudes towards them and their religion, Islam, disadvantages them both economically and socially. The Western media is alleged to have aggravated anti-Muslim sentiment since the 1990–1991 Gulf Crises, and after September 11, 2001 and the Bali tragedy in 2002, effectively divided the world into the Muslim terrorists (“evil”) and the civilised Christians (“good”). Within the framework of national interest and security, this paper examines whether Muslims' allegation of media bias is valid. If so, then, it will address the question, why is the media demonising this group of people, and who is to blame for this phenomenon—the media, its audience or the militant Islamic groups? This paper is based on primary and secondary sources including oral testimonies.
Flexible recruitment of semantic richness: context modulates body-object interaction effects in lexical-semantic processing

Body-object interaction (BOI) is a semantic richness variable that measures the perceived ease with which the human body can physically interact with a word's referent. Lexical and semantic processing is facilitated when words are associated with relatively more bodily experience. To date, BOI effects have only been examined in the context of one semantic categorization task (SCT; is it imageable? ). It has been argued that semantic processing is dynamic and can be modulated by context. We examined these influences by testing how task knowledge modulated BOI effects. Participants discriminated between the same sets of entity (high- and low-BOI) and action words in each of four SCTs. Task framing was manipulated: participants were told about one (is it an action? vs. is it an entity? ) or both (action or entity? vs. entity or action? ) categories of words in the decision task. Facilitatory BOI effects were only observed when participants knew that “entity” was part of the decision category. That BOI information was only useful when participants had expectations that entity words would be presented suggests a strong role for the decision context in lexical-semantic processing, and supports a dynamic view of conceptual knowledge.
Delta-like 4/Notch Signaling and Its Therapeutic Implications

Intense research efforts have been focused toward the identification of regulators of angiogenesis and the development of antiangiogenesis-based cancer therapies. The approval of anti–vascular endothelial growth factor (VEGF) monoclonal antibody (bevacizumab) for use in colorectal and lung cancer provides clinical validation for targeting angiogenesis for the treatment of cancer. Delta-like 4 (Dll4)–mediated Notch signaling represents another key pathway essential for vascular development. Recent studies yield substantial insights into the role of Dll4 in angiogenesis. Dll4 is downstream of VEGF signaling and its activation triggers a negative feedback that restrains the effects of VEGF. Attenuation of Dll4/Notch signaling results in chaotic vascular network with excessive branching and sprouting. In preclinical studies, blocking of Dll4/Notch signaling is associated with a paradoxical increase in tumor vessel density, yet causes marked growth inhibition due to functionally defective vasculature. Dll4 blockade holds promise as an additional strategy for angiogenesis-based cancer therapy, especially when resistance to and/or escape from existing therapies evolve.
Losing Hurts: The Happiness Impact of Partisan Electoral Loss

Partisan identity shapes social, mental, economic, and physical life. Using a novel dataset, we study the consequences of partisan identity by examining the immediate impact of electoral loss and victory on happiness and sadness. Employing a quasi-experimental regression discontinuity model we present two primary findings. First, elections strongly affect the immediate happiness/sadness of partisan losers, but minimally impact partisan winners. This effect is consistent with psychological research on the good-bad hedonic asymmetry, but appears to dissipate within a week after the election. Second, the immediate happiness consequences to partisan losers are relatively strong. To illustrate, we show that partisans are affected two times more by their party losing the 2012 U.S. Presidential Election than both respondents with children were to the Newtown shootings and respondents living in Boston were to the Boston Marathon bombings. We discuss implications regarding the centrality of partisan identity to the self and its well-being.
Optimization of RF- DC converter in micro energy harvester using voltage boosting network and bulk modulation technique for biomedical devices

This paper presents an optimization of the rectifier module for Radio Frequency (RF) energy harvesting system at 915 MHz band. This module converts the RF signal into direct-current voltage at the given frequency band to power ultra-low power bio-medical sensor. A transient analysis on various types of rectifier circuit is carried out to investigate their efficiency and sensitivity. To improve the power conversion efficiency, the voltage boosting network increases the voltage at the input of the full wave rectifier. By assuming the system is at resonance condition, the optimum parameters including the value of capacitance, inductance and load value are calculated. Simulation results show that passive component based circuit can significantly increase the RF input voltage and broaden the input range of the rectifier. The modified circuit enhances output voltage approximately 400 mV higher than output voltage from existing full wave rectifier at same level of input. This will help to increase the input range to be converted to dc output.
Longitudinal reliability of tract‐based spatial statistics in diffusion tensor imaging

Relatively little is known about reliability of longitudinal diffusion‐tensor imaging (DTI) measurements despite growing interest in using DTI to track change in white matter structure. The purpose of this study is to quantify within‐ and between session scan‐rescan reliability of DTI‐derived measures that are commonly used to describe the characteristics of neural white matter in the context of neural plasticity research. DTI data were acquired from 16 cognitively healthy older adults (mean age 68.4). We used the Tract‐Based Spatial Statistics (TBSS) approach implemented in FSL, evaluating how different DTI preprocessing choices affect reliability indices. Test‐Retest reliability, quantified as ICC averaged across the voxels of the TBSS skeleton, ranged from 0.524 to 0.798 depending on the specific DTI‐derived measure and the applied preprocessing steps. The two main preprocessing steps that we found to improve TBSS reliability were (a) the use of a common individual template and (b) smoothing DTI data using a 1‐voxel median filter. Overall our data indicate that small choices in the preprocessing pipeline have a significant effect on test‐retest reliability, therefore influencing the power to detect change within a longitudinal study. Furthermore, differences in the data processing pipeline limit the comparability of results across studies. Hum Brain Mapp 35:4544–4555, 2014. © 2014 Wiley Periodicals, Inc.