Miracle-dz/UniFAR-FTUs huggingface dataset:
Deletion of the Chloroplast-Localized Thylakoid Formation1 Gene Product in Arabidopsis Leads to Deficient Thylakoid Formation and Variegated Leaves1

Development of thylakoid membranes depends upon the transport of membrane vesicles from the chloroplast inner envelope and subsequent fusion of vesicles within the interior of the plastid. The Arabidopsis (Arabidopsis thaliana) Thylakoid formation1 (Thf1) gene product is shown here to control an important step required for the normal organization of these vesicles into mature thylakoid stacks and ultimately for leaf development. The Arabidopsis Thf1 gene encodes an imported chloroplast protein, as shown by in vitro import and localization of a Thf1-green fluorescent protein fusion product in transgenic plants. This gene is conserved in oxygenic photoautotrophs ranging from cyanobacteria to flowering land plants. Transcript levels for Thf1 are induced in the light and decrease under dark conditions, paralleling profiles of light-regulated nuclear genes involved in chloroplast function. Disruption of the Thf1 gene via T-DNA insertion results in plants that are severely stunted with variegated leaf patterns. Nongreen sectors of variegated leaves lacking Thf1 expression contain plastids that accumulate membrane vesicles on the interior and lack organized thylakoid structures. Green sectors of Thf1-disrupted leaves contain some chloroplasts that form organized thylakoid membranes, indicating that an inefficient compensatory mechanism supports thylakoid formation in the absence of Thf1. Genetic complementation of a Thf1 knockout line confirms the role of this gene in chloroplast and leaf development. Transgenic plants expressing the Thf1 gene in antisense orientation are stunted with altered thylakoid organization, especially in young seedlings. The data indicate that the Thf1 gene product plays a crucial role in a dynamic process of vesicle-mediated thylakoid membrane biogenesis.
An Asymptotically Optimal Policy for a Quantity-Based Network Revenue Management Problem

We consider a canonical revenue management problem in a network setting where the goal is to find a customer admission policy to maximize the total expected revenue over a fixed finite horizon. There is a set of resources, each of which has a fixed capacity. There are several customer classes, each with an associated arrival process, price, and resource consumption vector. If a customer is accepted, it effectively removes the resources that it consumes from the system. The exact solution cannot be obtained for reasonable-sized problems due to the curse of dimensionality. Several (approximate) solution techniques have been proposed in the literature. One way to analytically compare policies is via an asymptotic analysis where both resource sizes and arrival rates grow large. Many of the proposed policies are asymptotically optimal on the fluid scale. However, as we demonstrate in this paper, these policies may fail to be optimal on the more sensitive diffusion scale even for quite simple problem instances. We develop a new policy that achieves diffusion-scale optimality. The policy starts with a probabilistic admission rule derived from the optimization of the fluid model, embeds a trigger function that tracks the difference between the actual and expected customer acceptance, and sets threshold values for the trigger function, the violation of which invokes the reoptimization of the admission rule. We show that re-solving the fluid model, which needs to be performed at most once, is required for extending the asymptotic optimality from the fluid scale to the diffusion scale. We demonstrate the implementation of the policy by numerical examples.
Galleria mellonella as a model host to study Paracoccidioides lutzii and Histoplasma capsulatum

Non-mammalian models have been used to investigate fungal virulence. In this work we have explored the use of Galleria mellonella as an infection model for the pathogenic dimorphic fungi Histoplasma capsulatum and Paracoccidioides lutzii. In mammalian models these fungi cause similar infections, and disease outcomes are influenced by the quantity of the infective inocula. We describe a similar aspect in a G. mellonella model and characterize the pathogenesis features in this system. Infection with P. lutzii or H. capsulatum, in all inoculum used, killed larvae at 25 and 37°C. However, there was a lack of correlation between the number of yeast cells used for infection and the time to larvae death, which may indicate that the fungi induce protective responses in a dynamic manner as the lowest concentrations of fungi induced the most rapid death. For both fungi, the degree of larvae melanization was directly proportional to the inocula size, and this effect was visibly more apparent at 37°C. Histological evaluation of the larvae showed a correlation between the inoculum and granuloma-like formation. Our results suggest that G. mellonella is a potentially useful model to study virulence of dimorphic fungi.
Modeling business processes for PLM services integration in PLM system

Business Process modeling plays the central role in the business management through systems engineering from the perspective of enterprise modeling. Every organization prior to adapting an enterprise solution for productivity and efficiency needs to analyze the current processes within the organization and identify the required process efficiency and quality along with the transformation needed. The Object Management Group (OMG) Product Life Cycle Management (PLM) Services 2.0 prescribes specifications based on information and computational model for engineering objects that facilitate life cycle management. Besides, this specification also provides high level scenarios for the independent model rather than specific domain. For an efficient enterprise solution using PLM system, through PLM services, there is an emergent need for business process modelling since PLM system does not cover all the business processes and which converge towards the OMG PLM Services 2.0 specification with the required business change managements. This paper highlights key modeling issues for the business processes from the perspective of OMG PLM Services 2.0 using a case study in industrial context, and proposes a methodology for the transformation of BPM towards PLM Services. The proposed methodology satisfies the business process constraints for the PLM services.
The mediating effect of locus of control between role overload, job satisfaction and turnover intention

The primary objective of this research was to investigate the relationship between role overload, job satisfaction, turnover intention and participants' locus of control in a higher education institution. Specifically, the possible mediating effect of locus of control between overload and job satisfaction on the one hand, and turnover intention on the other, was investigated. A cross-sectional survey design was used and an availability sample was taken («=210). Measuring instruments for all variables were administered as well as a biographical questionnaire. Results indicated that job satisfaction was the strongest predictor of turnover intention. Locus of control was found to be a poor predictor of turnover intention and did not mediate the relationship between overload, job satisfaction and turnover intention.
LIMSI : Cross-lingual Word Sense Disambiguation using Translation Sense Clustering

We describe the LIMSI system for the SemEval-2013 Cross-lingual Word Sense Disambiguation (CLWSD) task. Word senses are represented by means of translation clusters in different languages built by a cross-lingual Word Sense Induction (WSI) method. Our CLWSD classifier exploits the WSI output for selecting appropriate translations for target words in context. We present the design of the system and the obtained results.
Logging the Search Self-Efficacy of Amazon Mechanical Turkers

Conducting focused but large-scale studies and experiments of user search behavior is highly desirable. Crowd-sourcing services such as the Amazon Mechanical Turk allow such studies to be conducted quickly and cheaply. They also have the potential to mitigate the problems associated with traditional experimental methods, in particular the relatively small and homogenous participant samples used in typical experiments. Our current research project addresses the relationship between searcher self-ecacy assessments and their strategies for conducting complex searches. In this work-in-progress paper, we describe our initial tests of using Amazon Mechanical Turk to conduct experiments in this area. We describe a platform for logging the actions taken by Turkers, and a questionnaire we conducted to assess search self-ecacy of average Turkers. Our results indicate Turkers have a similar range of search self-ecacy
Application of the bootstrap statistical method to the tau-decay-mode problem.

The bootstrap statistical method is applied to the discrepancy in the one-charged-particle decay modes of the tau lepton. This eliminates questions about the correctness of the errors ascribed to the branching-fraction measurements and the use of Gaussian error distributions for systematic errors. The discrepancy is still seen when the results of the bootstrap analysis are combined with other measurements and with deductions from theory. But the bootstrap method assigns less statistical significance to the discrepancy compared to a method using Gaussian error distributions.
Why Do Most Human Liver Cytosol Preparations Lack Xanthine Oxidase Activity?

When investigating the potential for xanthine oxidase (XO)-mediated metabolism of a new chemical entity in vitro, selective chemical inhibition experiments are typically used. Most commonly, these inhibition experiments are performed using the inhibitor allopurinol (AP) and commercially prepared human liver cytosol (HLC) as the enzyme source. For reasons detailed herein, it is also a common practice to perfuse livers with solutions containing AP prior to liver harvest. The exposure to AP in HLC preparations could obviously pose a problem for measuring in vitro XO activity. To investigate this potential problem, an HPLC-MS/MS assay was developed to determine whether AP and its primary metabolite, oxypurinol, are retained within the cytosol for livers that were treated with AP during liver harvest. Differences in enzymatic activity for XO and aldehyde oxidase (AO) in human cytosol that can be ascribed to AP exposure were also evaluated. The results confirmed the presence of residual AP (some) and oxypurinol (all) human liver cytosol preparations that had been perfused with an AP-containing solution. In every case where oxypurinol was detected, XO activity was not observed. In contrast, the presence of AP and oxypurinol did not appear to have an impact on AO activity. Pooled HLC that was purchased from a commercial source also contained residual oxypurinol and did not show any XO activity. In the future, it is recommended that each HLC batch is screened for oxypurinol and/or XO activity prior to testing for XO-mediated metabolism of a new chemical entity.
Clinical End Points in Coronary Stent Trials: A Case for Standardized Definitions

Background— Although most clinical trials of coronary stents have measured nominally identical safety and effectiveness end points, differences in definitions and timing of assessment have created confusion in interpretation. Methods and Results— The Academic Research Consortium is an informal collaboration between academic research organizations in the United States and Europe. Two meetings, in Washington, DC, in January 2006 and in Dublin, Ireland, in June 2006, sponsored by the Academic Research Consortium and including representatives of the US Food and Drug Administration and all device manufacturers who were working with the Food and Drug Administration on drug-eluting stent clinical trial programs, were focused on consensus end point definitions for drug-eluting stent evaluations. The effort was pursued with the objective to establish consistency among end point definitions and provide consensus recommendations. On the basis of considerations from historical legacy to key pathophysiological mechanisms and relevance to clinical interpretability, criteria for assessment of death, myocardial infarction, repeat revascularization, and stent thrombosis were developed. The broadly based consensus end point definitions in this document may be usefully applied or recognized for regulatory and clinical trial purposes. Conclusion— Although consensus criteria will inevitably include certain arbitrary features, consensus criteria for clinical end points provide consistency across studies that can facilitate the evaluation of safety and effectiveness of these devices.
Glucose deprivation induces mitochondrial dysfunction and oxidative stress in PC12 cell line

Glucose metabolism plays a pivotal role in many physiological and pathological conditions. To investigate the effect of hypoglycemia (obtained by glucose deprivation) on PC12 cell line, we analyzed the cell viability, mitochondrial function (assessed by MTT reduction, cellular ATP level, mitochondrial transmembrane potential), and the level of reactive oxygen species (ROS) after glucose deprivation (GD). Upon exposure to GD, ROS level increased and MTT reduction decreased immediately, intracellular ATP level increased in the first 3 hours, followed by progressive decrease till the end of GD treatment, and the mitochondrial transmembrane potential (ΔΨm) dropped after 6 hours. Both necrosis and apoptosis occurred apparently after 24 hours which was determined by nuclei staining with propidium iodide(PI) and Hoechst 33342. These data suggested that cytotoxity of GD is mainly due to ROS accumulation and ATP depletion in PC12 cells.
Harnessing the heart of big data.

The exponential increase in Big Data generation combined with limited capitalization on the wealth of information embedded within Big Data has prompted us to revisit our scientific discovery paradigms. A successful transition into this digital era of medicine holds great promise for advancing fundamental knowledge in biology, innovating human health, and driving personalized medicine; however, this will require a drastic shift of research culture in how we conceptualize science and use data. An e-transformation will require global adoption and synergism among computational science, biomedical research, and clinical domains. A scarce number of scientific investigations have innovated clinical diagnosis, prognosis, and therapeutics, despite decades of research and enormities of National Institutes of Health (NIH)–funded research dollars.1,2 This situation requires a global reassessment of whether linear thought processes and reductionistic approaches alone can describe biological processes in a way that translates to valuable information on human systems. Information gleaned from population science using large Big Data data sets has perpetuated a shift in the paradigm of how we define and investigate health and disease in the individual patient.3 We are recognizing the profound value in unorthodox data types and in the integration of diverse data to describe individuals to sufficient depths for discerning clinical outcomes. Biomedicine, along with other fields, has been awakened and awed by the digital wave of major corporations such as Google and Amazon, who have revolutionized the Internet roadmap through developing and refining sophisticated data analytics platforms to accurately describe individual human behavior.4 The reality in biomedical science is that there are zettabytes of high-quality data sitting idly on servers and in cloud infrastructures, and an abundance of biomedical knowledge lies hidden within, yet only a small fraction of this wealth has been harvested. There is an immediate need for data science to …
A zero-crossing edge detector with improved localization and robustness to image brightness and contrast manipulations

To characterize edges, this work proposes a zero-crossing detector that attempts to provide a more precise localization of edges together with robustness to brightness and contrast variation in images. Since the algorithm aims to be insensitive to image histogram manipulations, it is based on zero-crossings of the second derivative, and not on first derivative measurements. In order to provide good localization while preserving the true shape of the edges, the detector is based on precise mathematical expressions that represent image derivatives as a vector field, instead of using the Laplacian as a scalar approximation for the image second derivatives. This way, the proposed detector can be viewed as a Marr-Hildreth operator with a more exact mathematical formulation. Finally, to avoid false responses and provide thin edges, some additional checking is performed over the edge candidate points. The method showed good results when compared with well-known edge detectors.
An Empirical Examination of the Dual Threshold Model of Anger Expression

This exploratory study examines the suppression and expression of anger at work within the framework of Callister & Geddes' (2004) Dual Threshold Model. Data for the study were collected from surveys reflecting a critical incident methodology. Findings support the hypotheses that organizational silence leads to negative workplace outcomes, and expressed anger leads to positive workplace outcomes. There was partial support for the hypothesis that workplace displays of excessive anger negatively impact the offender and the situation that initially provoked the display. Also supported was the hypothesis that negative outcomes would increase when organizational members respond with sanctioning behavior toward the individual whose anger expression was viewed as excessive. Qualitative data were used to examine factors that encourage people to suppress or express their anger at work, as well as the types and frequency of supportive and sanctioning responses to anger displays by organizational observers.
Derivation of Human Induced Pluripotent Stem Cells for Cardiovascular Disease Modeling

The successful derivation of human induced pluripotent stem cells (hiPSCs) by dedifferentiation of somatic cells offers significant potential to overcome obstacles in the field of cardiovascular disease. hiPSC derivatives offer incredible potential for new disease models and regenerative medicine therapies. However, many questions remain regarding the optimal starting materials and methods to enable safe, efficient derivation of hiPSCs suitable for clinical applications. Initial reprogramming experiments were carried out using lentiviral or retroviral gene delivery methods. More recently, various nonviral methods that avoid permanent and random transgene insertion have emerged as alternatives. These include transient DNA transfection using plasmids or minicircles, protein transduction, or RNA transfection. In addition, several small molecules have been found to significantly augment hiPSC derivation efficiency, allowing the use of a fewer number of genes during pluripotency induction. We review these various methods for the derivation of hiPSCs, focusing on their ultimate clinical applicability, with an emphasis on their potential for use as cardiovascular therapies and disease-modeling platforms.
Comparison and Analysis of Greedy Energy-Efficient Scheduling Algorithms for Computational Grids

A computational grid is a distributed computational network, enabled with software that allows cooperation and the sharing of resources. The energy consumption of these large-scale distributed systems is an important problem. As our society becomes more technologically advanced, the size of these computational grids and energy consumption continue to increase. In this paper, we study the problem of optimizing energy consumption and makespan by focusing on different techniques to schedule the tasks to the computational grid. A computational grid is simulated using a wide range of task heterogeneity and size variety. The heuristics are used with the simulated computational grid and the results are compared extensively against each other.
NORM MANIPULATION, NORM EVASION: EXPERIMENTAL EVIDENCE

Using an economic bargaining game, we tested for the existence of two phenomena related to social norms, namely norm manipulation – the selection of an interpretation of the norm that best suits an individual – and norm evasion – the deliberate, private violation of a social norm. We found that the manipulation of a norm of fairness was characterized by a self-serving bias in beliefs about what constituted normatively acceptable behaviour, so that an individual who made an uneven bargaining offer not only genuinely believed it was fair, but also believed that recipients found it fair, even though recipients of the offer considered it to be unfair. In contrast, norm evasion operated as a highly explicit process. When they could do so without the recipient's knowledge, individuals made uneven offers despite knowing that their behaviour was unfair.
Space-time-Doppler block coding for correlated time-selective fading channels

Coping with time-selective fading channels is challenging but also rewarding, especially with multiantenna systems, where joint space-Doppler diversity and coding gains can be collected to enhance performance of wireless mobile links. These gains have not been quantified, and space-time coded systems maximizing joint space-Doppler benefits have not been designed. Based on a parsimonious basis expansion model for the underlying time-selective (and possibly correlated) channels, we quantify these gains in closed form. Furthermore, we develop space-time-Doppler coded systems that guarantee the maximum possible space-Doppler diversity, along with the largest coding gains within all linearly coded systems. Our three novel designs exploit knowledge of the maximum Doppler spread, and each offers a uniquely desirable tradeoff, including high spectral efficiency, low decoding complexity, and high performance. Our analytical results are confirmed by simulations and reveal the relative of merits of our three designs in comparison with an existing approach.
Privacy preserving trust authorization framework using XACML

Nowadays many organizations share sensitive services through open network systems and this raises the need for an authorization framework that can interoperate even when the parties have no pre-existing relationships. Trust negotiation is the process used to establish these first relationships, through the transfer of attributes, embedded in digital credentials, between the two parties. However, these attributes may themselves be considered sensitive and so may need protection from disclosure. In some environments, the policies that govern the protected services may also be considered sensitive and their release to arbitrary strangers may leak confidential business information. This paper describes a way to unify the protection of services, sensitive credentials and policies in a synchronized trustworthy manner. We propose a trust authorization framework (TAF) that builds on the capabilities of XACML to support the bilateral exchange of policies and credentials through trust negotiation
IGBT series connection under Active Voltage Control

In this paper an Active Voltage Control (AVC) technique is presented, for series connection of insulated-gate-bipolar-transistors (IGBT) and control of diode recovery. The AVC technique can control the switching trajectory of an IGBT according to a pre-set reference signal. In series connections, every series connected IGBT follows the reference and so that the dynamic voltage sharing is achieved. For the static voltage balancing, the AVC technique can clamp the highest collector-to-emitter voltage to a pre-set clamping voltage level. By selecting the value of the clamping voltage, the difference among series connected IGBTs can be controlled in an accepted range. Another key advantage for AVC is that by changing the reference signal at turn-on, the diode recovery can be optimized.