Miracle-dz/UniFAR-FTUs huggingface dataset:
The CCL2/CCR2 Axis Enhances Vascular Cell Adhesion Molecule-1 Expression in Human Synovial Fibroblasts

Background Chemokine ligand 2 (CCL2), also known as monocyte chemoattractant protein-1 (MCP-1), belongs to the CC chemokine family that is associated with the disease status and outcomes of osteoarthritis (OA). Here, we investigated the intracellular signaling pathways involved in CCL2-induced vascular cell adhesion molecule-1 (VCAM-1) expression in human OA synovial fibroblasts (OASFs). Methodology/Principal Findings Stimulation of OASFs with CCL2 induced VCAM-1 expression. CCL2-mediated VCAM-1 expression was attenuated by CCR2 inhibitor (RS102895), PKCδ inhibitor (rottlerin), p38MAPK inhibitor (SB203580), and AP-1 inhibitors (curcumin and tanshinone IIA). Stimulation of cells with CCL2 increased PKCδ and p38MAPK activation. Treatment of OASFs with CCL2 also increased the c-Jun phosphorylation and c-Jun binding to the AP-1 element on the VCAM-1 promoter. Moreover, CCL2-mediated CCR2, PKCδ, p38MAPK, and AP-1 pathway promoted the adhesion of monocytes to the OASFs monolayer. Conclusions/Significance Our results suggest that CCL2 increases VCAM-1 expression in human OASFs via the CCR2, PKCδ, p38MAPK, c-Jun, and AP-1 signaling pathway. The CCL2-induced VCAM-1 expression promoted monocytes adhesion to human OASFs.
Gene-to-metabolite network for biosynthesis of lignans in MeJA-elicited Isatis indigotica hairy root cultures

Root and leaf tissue of Isatis indigotica shows notable anti-viral efficacy, and are widely used as “Banlangen” and “Daqingye” in traditional Chinese medicine. The plants' pharmacological activity is attributed to phenylpropanoids, especially a group of lignan metabolites. However, the biosynthesis of lignans in I. indigotica remains opaque. This study describes the discovery and analysis of biosynthetic genes and AP2/ERF-type transcription factors involved in lignan biosynthesis in I. indigotica. MeJA treatment revealed differential expression of three genes involved in phenylpropanoid backbone biosynthesis (IiPAL, IiC4H, Ii4CL), five genes involved in lignan biosynthesis (IiCAD, IiC3H, IiCCR, IiDIR, and IiPLR), and 112 putative AP2/ERF transcription factors. In addition, four intermediates of lariciresinol biosynthesis were found to be induced. Based on these results, a canonical correlation analysis using Pearson's correlation coefficient was performed to construct gene-to-metabolite networks and identify putative key genes and rate-limiting reactions in lignan biosynthesis. Over-expression of IiC3H, identified as a key pathway gene, was used for metabolic engineering of I. indigotica hairy roots, and resulted in an increase in lariciresinol production. These findings illustrate the utility of canonical correlation analysis for the discovery and metabolic engineering of key metabolic genes in plants.
Nonconvex spectral algorithm for solving BMI on the reduced order H∞ control

The design of reduced-order H∞ control can be transformed into an optimization problem with bilinear matrix inequality (BMI) constraints, which is an NP-hard problem. We propose a method to equivalently transfer the BMI constraint into a convex LMI constraint plus a matrix-rank constraint. The optimization with matrix-rank constraint is iteratively solved by a sequence of semidefinite programming (SDP) problems. Simulations on several benchmark systems show that our algorithm is practical and efficient.
Financial reporting paradigms for financial instruments

Purpose – It is well known that once regulatory bodies adopt a financial reporting paradigm, it becomes the guiding principle for accounting regulation. This paradigm itself in the field of accounting represents the starting point of the research. The purpose of this paper is to focus on the specific case of the Czech Republic and Romania, namely on aspects concerning regulations in the field of financial instruments.Design/methodology/approach – The authors have approached an a priori economic analysis of national regulations in correlation with international standards inferences. In doing so, they have identified several key issues, which need to be discussed when thoroughly analyzing accounting regulations for financial instruments. Furthermore, the authors have used statistical indicators in order to determine the degree of similarities and dissimilarities between the two national accounting systems and also in correspondence with the international referential.Findings – The results of the performed a.
Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM

Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM). Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS), segmented PsePSSM, and segmented autocovariance transformation (ACT) based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640) are adopted in this paper. Then a 700-dimensional (700D) feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA). To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.
The management of the early stages of restructuring in a tertiary-education institution: An organisational commitment perspective

Restructuring in business firms is often characterised by uncertainty, anxiety, low morale, tardy job performance and high levels of absenteeism and staff turnover. Restructuring has recently been extended to tertiary education, but its effects on the higher education environment have not been thoroughly investigated. This study investigates the impact of restructuring (mergers) on the organisational commitment, job performance and intent to resign of tertiary education staff, as well as the relationship between selected antecedents (commitment to top management and satisfaction with career factors, monetary remuneration, fringe benefits, relations with peers and growth needs) and organisational commitment. The results show that the respondents, during the early stages of restructuring, exhibit low levels of organisational commitment, commitment to top management and satisfaction with monetary remuneration, fringe benefits and career factors. They also report high levels of satisfaction with growth factors (opportunities for training and development), relations with peers and performance intentions, and low levels of intentions to resign. Multiple regression analyses reveal that organisational commitment is positively related to performance intentions and negatively related to intent to resign. The results also show that commitment to top management and satisfaction with fringe benefits, peer relations and career factors were positively related to organisational commitment. Neither satisfaction with monetary remuneration nor the satisfaction of growth needs was significantly related to organisational commitment. The managerial implications of these findings are discussed.
Combining optical tweezers and scanning probe microscopy to study DNA–protein interactions

We present the first results obtained with a new instrument designed and built to study DNA–protein interactions at the single molecule level. This microscope combines optical tweezers with scanning probe microscopy and allows us to locate DNA‐binding proteins on a single suspended DNA molecule. A single DNA molecule is stretched taut using the optical tweezers, while a probe is scanned along the molecule. Interaction forces between the probe and the sample are measured with the optical tweezers. The instrument thus enables us to correlate mechanical and functional properties of bound proteins with the tension within the DNA molecule. The typical friction force between a micropipette used as probe and a naked DNA molecule was found to be <1 pN. A 16 μm DNA molecule with ∼10–15 digoxygenin (DIG) molecules located over a 90 nm range in the middle of the DNA was used as a model system. By scanning with an antidigoxygenin (α‐DIG) antibody‐coated pipette we were able to localize these sites by exploiting the high binding affinity between this antibody–antigen pair. The estimated experimental resolution assuming an infinitesimally thin and rigid probe and a single α‐DIG/DIG bond was 15 nm. Microsc. Res. Tech., 2006. © 2006 Wiley‐Liss, Inc.
Unsupervised BCI Calibration as Possibility for Communication in CLIS Patients ?

In this paper we present first results that a Brain-Computer Interface (BCI) can be calibrated online in a completely unsupervised manner. Thereby it is possible to provide a user with contingent feedback without the need for any goal-directed action. Since the extinction of goal-directed thinking is the assumed cause, why there are no reports of successful BCI communication in patients suffering from complete locked-in syndrome (CLIS), we discuss if unsupervised calibration could be used to enable communication in those patients.
The Yale book of quotations

This reader-friendly volume contains more than 12,000 famous quotations, arranged alphabetically by author. It is unique in its focus on American quotations and its inclusion of items not only from literary and historical sources but also from popular culture, sports, computers, science, politics, law, and the social sciences. Anonymously authored items appear in sections devoted to folk songs, advertising slogans, television catchphrases, proverbs, and others. For each quotation, a source and first date of use is cited. In many cases, new research for this book has uncovered an earlier date or a different author than had previously been understood. (It was Beatrice Kaufman, not Sophie Tucker, who exclaimed, "I've been poor and I've been rich. Rich is better! " William Tecumseh Sherman wasn't the originator of "War is hell! " It was Napoleon.) Numerous entries are enhanced with annotations to clarify meaning or context for the reader. These interesting annotations, along with extensive cross-references that identify related quotations and a large keyword index, will satisfy both the reader who seeks specific information and the curious browser who appreciates an amble through entertaining pages.
The Semantic Space of Vehicle Sounds - An Approach to Develop a Semantic Differential in View of Customer Perceptions

Sound quality evaluation of the vehicle sound is a complex process. Physical measures are not sufficient to describe and understand this process and they can only give superficial cues. Psychoacoustical parameters and measurements also do not allow a general description of the vehicle sound quality. The quality evaluation of the customers is based on their perception, interpretation and expectations. The aim of this study is to generate the semantic space of vehicle sounds. In other words, a number of attributes relating to the perception and quality of vehicle sound will be elicited. This semantic space will be the basis of the development of attribute scales (Semantic Differential). Therefore our aim is to find the common descriptive language of the customers which is appropriate for the vehicle sound quality evaluation. An approach was developed and applied in this study. The steps of this approach include a thinking aloud test (free verbal remarking interview), the evaluation of the terms according to their suitability in describing acoustically perceptible vehicle properties by all subjects, testing the understandability of the attributes for all subjects, control the completeness of the semantic database to describe the vehicle sounds conducting a similarity experiment, testing the relevance and the redundancy of the attributes. At the end of the investigation eight different sets of attributes were developed for eight different driving conditions. Each set contains 18 to 36 attributes.
Myocardial first pass perfusion: Steady‐state free precession versus spoiled gradient echo and segmented echo planar imaging

The imaging sequences used in first pass (FP) perfusion to date have important limitations in contrast‐to‐noise ratio (CNR), temporal and spatial resolution, and myocardial coverage. As a result, controversy exists about optimal imaging strategies for FP myocardial perfusion. Since imaging performance varies from subject to subject, it is difficult to form conclusions without direct comparison of different sequences in the same subject. The purpose of this study was to directly compare the saturation recovery SSFP technique to other more commonly used myocardial first pass perfusion techniques, namely spoiled GRE and segmented EPI. Differences in signal‐to‐noise ratio (SNR), CNR, relative maximal upslope (RMU) of signal amplitude, and artifacts at comparable temporal and spatial resolution among the three sequences were investigated in computer simulation, contrast agent doped phantoms, and 16 volunteers. The results demonstrate that SSFP perfusion images exhibit an improvement of approximately 77% in SNR and 23% in CNR over spoiled GRE and 85% SNR and 50% CNR over segmented EPI. Mean RMU was similar between SSFP and spoiled GRE, but there was a 58% increase in RMU with SSFP versus segmented EPI. Magn Reson Med, 2005. © 2005 Wiley‐Liss, Inc.
Alcohol Consumption and Breast Cancer Survival: A Meta- analysis of Cohort Studies.

BACKGROUND AND OBJECTIVES Evidence for associations between alcohol consumption with breast cancer survival are conflicting, so we conducted the present meta-analysis. METHODS Comprehensive searches were conducted to find cohort studies that evaluated the relationship between alcohol consumption with breast cancer survival. Data were analyzed with meta-analysis software. RESULTS We included 25 cohort studies. The meta-analysis results showed that alcohol consumption was not associated with increased breast cancer mortality and recurrence after pooling all data from highest versus lowest comparisons. Subgroup analyses showed that pre-diagnostic or post-diagnostic consumpotion, and ER status did not affect the relationship with breast cancer mortality and recurrence. Although the relationships of different alcohol consumption with breast cancer mortality and recurrence were not significant, there seemed to be a dose-response relationship of alcohol consumption with breast cancer mortality and recurrence. Only alcohol consumption of >20 g/d was associated with increased breast cancer mortality, but not with increased breast cancer recurrence. CONCLUSION Although our meta-analysis showed alcohol drinking was not associated with increased breast cancer mortality and recurrence, there seemed to be a dose-response relationship of alcohol consumption with breast cancer mortality and recurrence and alcohol consumption of >20 g/d was associated with increased breast cancer mortality.
Design based research to create instructional design templates for learning objects

One such educational research problem is the process of creating learning objects (LOs). Learning objects (LOs) have become valuable teaching and learning tools in a variety of instructional contexts (Bratina, 2002, Boyle, 2003, Wang, 2008). Creation of LOs involves multiple interactions between stakeholders from various domains such as the subject matter, instructional design, visual communication and software development (Weerasinghe, 2007). During the LO creation process, templates are used to generate products such as Instructional design document, storyboard and animation design document, which facilitate the interaction between the stakeholders. To make the process more efficient, the templates need to be iteratively refined and tested. The research method chosen to address this problem should facilitate the observation of the interactions between multiple stakeholders and the iterative testing of the products.
Hybrid Approaches for Stock Price Prediction

—There is a wide acceptance of benefit of the synergy effect. The object of this paper is to investigate whether a hybrid approach combining different stock prediction approaches together can dramatically outperform the single approach and compare the performance of different hybrid approaches. The hybrid model includes three well-researched prediction algorithms: back propagation neural network (BPNN), adaptive network-based fuzzy neural inference system (ANFIS) and support vector machine (SVM). First, we utilize them independently to single-step forecast the stock price, and then integrate the three forecasts into a final result by a combining strategy. Two different combining methods are investigated. The first method is a linear combination of the three forecasts. The second method combines them by a neural network. We have all of the algorithms experiment on the S&P500 Index. The experiment verifies that by combining the single algorithm considerately, a better performance can be received.
Multiobjective Evolution of Neural Controllers and Task Complexity

Robots operating in everyday life environments are often required to switch between different tasks. While learning and evolution have been effectively applied to single task performance, multiple task performance still lacks methods that have been demonstrated to be both reliable and efficient. This paper introduces a new method for multiple task performance based on multiobjective evolutionary algorithms, where each task is considered as a separate objective function. In order to verify the effectiveness, the proposed method is applied to evolve neural controllers for the Cyber Rodent (CR) robot that has to switch properly between two distinctly different tasks: 1) protecting another moving robot by following it closely and 2) collecting objects scattered in the environment. Furthermore, the tasks and neural complexity are analyzed by including the neural structure as a separate objective function. The simulation and experimental results using the CR robot show that the multiobjective-based evolutionary method can be applied effectively for generating neural networks that enable the robot to perform multiple tasks simultaneously.
Performance of (D,d)-OM Search

In Opponent-Model search (OM search) perfect knowledge of the opponent's evaluation function is assumed. This knowledge may lead to the conclusion that the opponent intends to make an error in a given position. As a consequence the error may be exploited to the advantage of the player possessing the knowledge. In such an OM-search model, it is implicitly assumed that both players search to the same depth. The current paper describes a generalization of OM search, called (D; d)-OM search, in which the di erence of the search depth reached by both players is taken into account. The algorithm, the main characteristics and an analysis of the e ciency are given in detail. Moreover, a game-tree model including an opponent model is constructed. Finally, preliminary results are given using that model and using Othello.
Model-based and empirical performance analyses for passenger positioning algorithms in a specific bus cabin environment

Localization methods play an increasing role in many of today's Intelligent Transportation Systems (ITS). In the context of this work we concentrate on improving the localization accuracy of passengers in public transport vehicles, e.g. as part of automated registration, counting or ticketing systems. In these applications each passenger's ticket could be designed as a mobile wireless sensor node, which is registered to be inside or outside the vehicle using a network of fixed anchor nodes inside only. We shortly describe two specific positioning approaches (SMDS, GBP) out of a variety of methods. A set of measurements conducted in a realistic bus cabin environment is then used to analyze the performance of both algorithms. The accuracy of the proposed GBP-estimator is compared with a previously studied SMDS-estimator, particularly in severe multipath environments like in the given passenger cabin.
Children at Work

In this chapter we consider childhood employment in a life course perspective. We seek to understand how family background, childhood experiences and orientations, and macrolevel changes (e.g., economic shocks such as the Great Recession) influence the timing of entry into the world of work and the characteristics of first jobs; how childhood and adolescent work experiences are linked to school achievement, other work activities, and problem behaviors; and the potential long-term consequences of early involvements in paid work for health and well-being, as well as engagement and success in work, school, and family. The chapter is divided into three parts: In the first part we discuss research on the correlates and consequences of youth work in the United States, highlighting four major perspectives on this topic. In the second section, we review the literature on child and adolescent employment in an international context, discussing some major themes in this diverse literature. Our goal here is not to provide an exhaustive review of this literature, but instead to highlight some of the unique situations that young workers in developing countries face as they leave school and enter the labor market. In the final section, we discuss potential areas of new research on youth employment, such as the impact of the global recession on child and youth work in both the United States and worldwide, further examination of how different types and qualities of work relate to children and adolescent outcomes, and more studies that consider diverse trajectories of school and work involvement during the early occupational career. Keywords: child and adolescent employment; life course perspective; school-to-work transition
Operations Now: Supply Chain Profitability and Performance

UNIT ONE: FOUNDATIONS FOR SUCCESS Chapter 1: Introduction: Why Operations Management? Chapter 2: Profitability: Business Success from Operations Success Chapter 3: Strategy and Value: Competing through Operations Chapter 4: Processes: Turning Resources into Capabilities UNIT TWO: COMPONENTS OF VALUES Chapter 5: Cost: The Price of Value Creation Chapter 6: Quality: Meeting Customer Expectations Chapter 7: Quality Tools: From Process Performance to Process Perfection Chapter 8: Timeliness: Scheduling and Project Management UNIT THREE: MANAGING RESOURCES TO CREATE VALUE Chapter 9: Supply Chain Management: Managing Business to Business Interactions Chapter10: Demand Forecasting: Building the Foundation for Resource Planning Chapter 11: Inventory: Managing to Meet Demand Chapter 12: Logistics: Positioning Goods in the Supply Chain Chapter 13: Lean Systems: Eliminating Waste through the Supply Chain Chapter 14: Capacity: Matching Productive Resources to Demand Chapter 15: Constraint Management: Simplifying Complex Systems Chapter 16: Facilities: Making Location and Layout Decisions Chapter 17: Workforce: Optimizing Human Capital