Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Multivariate Empirical Mode Decomposition in EEG signals for Subject Independent Affective States Classification

Physiological signals, EEG in particular, are inherently noisy and non-linear in nature which are challenging to work with using conventional linear signal processing methods. In this paper, we are adopting a new signal processing method, Multivariate Empirical Mode Decomposition, as a preprocessing method to reconstruct EEG signals according to its instantaneous frequencies. To test its effectiveness, we applied this signal reconstruction technique on EEG signals for a 2-dimensional affect states classification application. To evaluated the proposed EEG signal processing system, a three-class classification experiment were carried out on the Emobrain dataset from eNTERFACE’06 with K-nearest neighbours (KNN) and Linear Discriminate Analysis (LDA) as classifiers. A leave-one-subject out cross validation process were used and an averaged correct classification rate of 90.77% were achieved. Another main contribution of this paper was inspired by the growth of non-medical grade EEG headsets and its potential in advanced human-computer interface design. However, to reduce cost and invasiveness, consumer grade EEG headsets have far less number of electrodes. In this paper, we used emotion recognition as a case study, and applied Genetic Algorithm to systematically select the critical channels (or sensor locations) for this application. The results of this study provide much needed insights on sensor configuration for future consumer-grade EEG headset design.
The role that inactivation of GSK 3 isoforms resulting from Ser 9 / Ser 21 phosphorylation plays in insulin-signalling and Wnt-mediated-catenin stabilisation defined by knockin analysis

The role that inactivation of GSK3 isoforms resulting from Ser9/Ser21 phosphorylation plays in insulin-signalling and Wnt-mediated -catenin stabilisation defined by knockin analysis. By Edward J. McManus, Kei Sakamoto, Laura J Armit, Leah Ronaldson, Natalia Shpiro, Rodolfo Marquez and Dario R. Alessi MRC Protein Phosphorylation Unit and Division of Biological Chemistry and Molecular Mircrobiology, School of Life Sciences, MSI/WTB complex, University of Dundee, Dow Street, Dundee DD1 5EH, Scotland.
Pathologic response and long-term follow-up in breast cancer patients treated with neoadjuvant chemotherapy: a comparison between classifications and their practical application.

CONTEXT Breast cancer is increasingly treated with neoadjuvant chemotherapy to improve surgical resectability and evaluate tumor response, which is assessed histopathologically. Several histopathologic classification systems have been previously described for assessment of treatment response. OBJECTIVES To test performance in a side-by-side comparison of several histopathologic classification systems after neoadjuvant chemotherapy with clinical outcome. DESIGN Sixty-two patients were enrolled in a randomized trial receiving sequential neoadjuvant chemotherapy with doxorubicin and paclitaxel. Histologic sections from the patients' tumors sampled before (core biopsy) and after treatment (excision or mastectomy) were reviewed. Histologic response was assessed following National Surgical Adjuvant Breast and Bowel Project protocol B18, Miller-Payne grading, Sataloff tumor and nodes, Residual Cancer Burden (RCB), and Residual Disease in Breast and Nodes (RDBN). Pathologic classification results were correlated with survival using Kaplan-Meier and Cox hazards regression with a median follow-up of 93 months. RESULTS RDBN was associated with distant disease-free survival by univariate and multivariate analysis (P = .01 and .004, respectively), as were lymph node metastases (P = .02 and .01, respectively). Five patients (8%) had complete pathologic response after neoadjuvant chemotherapy, and none of them relapsed during the study period. Survival was shorter among patients with higher Residual Cancer Burden scores, but the associations were not significant. Miller-Payne grading and Sataloff tumor scores were not correlated with survival. CONCLUSIONS Evaluation of breast specimens after neoadjuvant chemotherapy by the composite index RDBN correlates with long-term outcome. The residual disease in breast and nodes system is suitable for routinely processed pathology cases. This study confirms the importance of lymph node status after neoadjuvant chemotherapy and favorable outcome in patients with pathologic complete response.
Nursing Students in a Global Learning Environment

Purpose: Two tools were created to help international students to better understand culture by becoming more astute observers of nonverbal behaviors, particularly behaviors depicting emotions among Norwegian students. Design/Method: The two tools were a trilingual list of words illustrating emotions and an exercise with images to practice verbalizing their observations of emotional expression. Findings: Students compared the subdued behaviors of Norwegians to the Israelis’ very vivid behaviors. The intense emotional expression of Israelis influenced their interpretations. By making comparisons and through the experiences with Israelis, they learned more about culture and their own emotional expression. Discussions and Conclusions: Creative strategies can contribute to students understanding and reflection of patients in a different culture. Implications for Practice: Encouraging students to grasp the nuances of emotional expression is part of understanding a different culture. Students, like faculty, learn that self-exploration is an evolving process that requires checking out one’s assumptions and interpretations.
Changes in electromyographic amplitudes but not latencies occur with endotracheal tube malpositioning during intraoperative monitoring for thyroid surgery: Implications for guidelines

During intraoperative neural monitoring (IONM) in thyroid and parathyroid surgery, endotracheal (ET) tube migration can result in a decrease in vocalis electromyographic (EMG) amplitude without a concordant latency elevation during stimulation of the recurrent laryngeal nerve (RLN).
Proposing a Knowledge Management System (KMS) Architecture to Promote Knowledge Sharing among Employees

Knowledge is a strategic resource for knowledge intensive organizations like commercial banks. However, the use of knowledge as resource depends on an organization’s ability to select, capture, store, disseminate and apply its knowledge resources. This organizational capability is created if the organization undertakes explicit initiatives to establish and sustain a KMS as one of its core business functions. An empirical investigation of the Commercial Bank of Ethiopia (CBE) shows that there is no explicit initiative or responsible unit to manage its knowledge resources. This study uses a design science research method to investigate the problems KM in CBE and propose KMS architecture which is believed, when implemented, to solve current problems. The main theoretical contribution of the study is that it demonstrates how to design a KMS architecture using system analysis and ontology methods. The paper has also implication for practice as it suggests solutions for observed problems and ways to increase CBE’s capability to use its knowledge resources.
Evaluation the Effect of Implementing Business Intelligence on Customer Relationship Management Success

Today, due to advances in information technology, improving management approaches and expansion of competitive markets, markets are overloaded with excess supply. These conditions have been lead to consider clients as the real rulers of the market. In this economic climate of customer-focused, organizations have to moving from focus on the product to focus on the customers and manage their behavior, in order to provide maximum efficiency for organization and their customers. Therefore, it is important that managers should make good use of the information systems instruments, such as Business Intelligence (BI) to extract desired information form enormous data volumes quickly in order to increase the profits of their organizations. This study has tried to investigate the effect of implementing BI on improving Customer Relationship Management (CRM) in Pars Modir's Research and Scientific Center. To this end,a conceptual model has been formulated that in which information technology, knowledge management and organizational conduciveness towards BI were identified as input factors, while customer orientation was modeled as outcome factor. Our research hypotheses were examined using Partial Least Squares (PLS) technique and T-value statistic. Results supported our research model, showing that all input factors were positively and significantly affected the success of CRM.
Generator Maintenance Scheduling Of Power System Using Hybrid Technique

This paper presents generator maintenance scheduling of a power system based on minimization of the objective function considering the economical and reliable operation of a power system while satisfying the network constraints along with crew/manpower, generation limits, precedence constraints, demanded load, maintenance window, loss of load probability and reliability constraints. Optimization was carried out on a practical thermal power plant consisting of 19 generating units, over a 25 weeks planning horizon.
Isolation of a keratinolytic proteinase from Trichophyton mentagrophytes with enzymatic activity at acidic pH

A keratinolytic proteinase with enzyme activity at acidic pH was isolated from culture filtrates of Trichophyton mentagrophytes, a major pathogenic fungus of dermatophytosis. The molecular weight of the proteinase was estimated to be 41,000 by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and 38,000 by gel filtration. The isoelectric point was determined to be 3.9. The proteinase had a pH optimum of 4.5 for keratin and 5.5 for hemoglobin. This enzyme hydrolyzed the synthetic chymotrypsin substrate Suc-Ala-Ala-Pro-Phe-MCA (Km, 0.59 mM), and its activity was strongly inhibited by chymostatin. Previously reported proteinases from dermatophytes have had enzyme activities in neutral or alkaline pH; however, healthy skin has a weakly acidic pH. Thus, the purified proteinase which has an optimal activity at acidic pH and hydrolyzes skin constituents could be an important virulence factor in dermatophytosis.
Optimizing Two Targets for Calibrating a Broadband Multibeam Sonar

The new Simrad MS70 multibeam sonar has a nominal total bandwidth of 70-120 kHz. Scientific applications of this, as in fisheries and other ecological research, require calibration. The standard-target method is suitable. Design criteria for the standard target are that this be robust and dense, with a mass of order several kilograms and with target strength in the nominal range from -35 to -30 dB. Candidate targets necessarily contain resonances in their backscattering spectra. Two targets are therefore proposed to cover the total band in piecewise fashion. For the selected material of tungsten carbide with 6% cobalt binder, the optimized sphere diameters are 75 and 84 mm. Detailed computations of the respective target strength spectra and sensitivity to variations in medium temperature are given with respect to the reference ambient temperature 8 deg C and salinity 33 ppt
Construction, Deconstruction, and Reconstruction

The authors’ goals are to examine the evolution of the concept of successful aging and its relevance to nursing science and practice. First, the history of positivist construction of aging in light of disengagement and activity theories is presented. Second, an analysis of the postmodern deconstruction of aging is illustrated with the development of the ageism phenomenon. Third, the beginning of the reconstruction of aging is presented and exemplified by Troutman’s middle-range nursing theory of successful aging, as connected to Roy’s model. Finally, ways in which these theories can be made applicable to nursing practice and research are proposed.
Density-based graph model summarization: Attaining better performance and efficiency

Several algorithms based on PageRank algorithm have been proposed to rank the document sentences in the multidocument summarization field and LexRank and T-LexRank algorithms are well known examples. In literature different concepts such as weighted inter-cluster edge, cluster-sensitive graph model and document-sensitive graph model have been proposed to improve LexRank and T-LexRank algorithms (e.g. DsR-G, DsR-Q) for multi-document summarization. In this paper, a density-based graph model for multi-document summarization is proposed by adding the concept of density to LexRank and T-LexRank algorithms. The resulting generic multi-document summarization systems, DensGS and DensGSD were evaluated on DUC 2004 while the query-based variants, DensQS, DensQSD were evaluated on DUC 2006, DUC 2007 and TAC 2010 task A. ROUGE measure was used in the evaluation. Experimental results show that density concept improves LexRank and T-LexRank algorithms and outperforms previous graph-based models (DsR-G and DsR-Q) in generic and query-based multi-document summarization tasks. Furthermore, the comparison of the number of iterations indicates that the density-based algorithm is faster than the other algorithms based on PageRank.
Maternal zinc deficiency reduces NMDA receptor expression in neonatal rat brain, which persists into early adulthood

Prenatal and early postnatal zinc deficiency impairs learning and memory and these deficits persist into adulthood. A key modulator in this process may be the NMDA receptor; however, effects of zinc deficiency on the regulation of NMDA receptor activity are not well understood. Female Sprague‐Dawley rats were fed diets containing 7 (zinc deficient, ZD), 10 (marginally zinc deficient, MZD) or 25 (control) mg Zn/g diet preconception through postnatal day (PN) 20, at which time pups were weaned onto their maternal or control diet. Regulation of NMDA receptor expression was examined at PN2, PN11, and PN65. At PN2, expression of whole brain NMDA receptor subunits NR1, NR2A, and NR2B was lower in pups from dams fed ZD and MZD compared to controls, as analyzed using relative RT–PCR and immunoblotting. At PN11, whole brain and hippocampi NR1, NR2A, NR2B and PSA‐NCAM (polysialic acid–neural cell adhesion molecule) expression and the number of PSA‐NCAM immunoreactive cells were lower in pups from dams fed ZD compared to controls. Whole brain brain‐derived neurotrophic factor (BDNF) and nerve growth factor (NGF) concentrations were lower in pups from dams fed ZD or both low zinc diets, respectively. Whole brain NR1 expression remained lower in previously zinc‐deficient rats at PN65. These data indicate potential mechanisms through which developmental zinc deficiency can impair learning and memory later in life.
Different minimally important clinical difference (MCID) scores lead to different clinical prediction rules for the Oswestry disability index for the same sample of patients

Abstract Background: Minimal clinically important difference (MCID) scores for outcome measures are frequently used evidence-based guides to gage meaningful changes. There are numerous outcome instruments used for analyzing pain, disability, and dysfunction of the low back; perhaps the most common of these is the Oswestry disability index (ODI). A single agreed-upon MCID score for the ODI has yet to be established. What is also unknown is whether selected baseline variables will be universal predictors regardless of the MCID used for a particular outcome measure. Objective: To explore the relationship between predictive models and the MCID cutpoint on the ODI. Setting: Data were collected from 16 outpatient physical therapy clinics in 10 states. Design: Secondary database analysis using backward stepwise deletion logistic regression of data from a randomized controlled trial (RCT) to create prognostic clinical prediction rules (CPR). Participants and Interventions: One hundred and forty-nine patients with low back pain (LBP) were enrolled in the RCT. All were treated with manual therapy, with a majority also receiving spine-strengthening exercises. Results: The resultant predictive models were dependent upon the MCID used and baseline sample characteristics. All CPR were statistically significant (P < 001). All six MCID cutpoints used resulted in completely different significant predictor variables with no predictor significant across all models. Limitations: The primary limitations include sub-optimal sample size and study design. Conclusions: There is extreme variability among predictive models created using different MCIDs on the ODI within the same patient population. Our findings highlight the instability of predictive modeling, as these models are significantly affected by population baseline characteristics along with the MCID used. Clinicians must be aware of the fragility of CPR prior to applying each in clinical practice.
Dependence of cytosolic calcium in differentiating rat pheochromocytoma cells on calcium channels and intracellular stores.

1. The rat clonal pheochromocytoma cell line (PC12) was used to study changes in the free intracellular Ca2+ concentration [( Ca2+]i) that are related to the distribution of L‐type (dihydropyridine‐sensitive) and N‐type (omega‐conotoxin‐sensitive) calcium channels during nerve growth factor (NGF)‐induced outgrowth of neurites. Changes in [Ca2+]i during K+ depolarization were recorded by means of Fura‐2 single‐cell microfluorimetry. 2. The basal [Ca2+]i of cells at rest was not altered by long‐term treatment with NGF, neither in the cell bodies nor in the growth cones. K+ depolarization of the cells caused a rise in [Ca2+]i. 3. The dihydropyridine (DHP) nifedipine alone, or together with omega‐conotoxin (omega‐CgTX), were similarly effective in inhibiting the K(+)‐induced increase in [Ca2+]i in untreated and NGF‐treated cell bodies, arguing for a preferential distribution of L‐type Ca2+ channels in this cell area. By contrast, after 6‐7 days exposure to NGF the K(+)‐induced initial transient rise of [Ca2+]i in growth cones was very sensitive to omega‐CgTX, whereas nifedipine affected only the sustained rise. 4. PC12 cells also contain caffeine‐ and inositol trisphosphate (IP3)‐sensitive intracellular Ca2+ stores. Addition of 30 mM‐caffeine caused a fast transient rise in [Ca2+]i. The extent of filling of the caffeine‐sensitive pool affected basal [Ca2+]i. These Ca2+ storage sites were empty under normal culture conditions. However, a single K+ depolarization caused filling of the stores, followed by spontaneous depletion (50% in about 5 min) after wash‐out of high [K+]o. When the caffeine‐sensitive stores were empty, the rise in [Ca2+]i was attenuated during submaximal depolarization. Caffeine‐sensitive Ca2+ stores were also present in some growth cones, though with much smaller capacities than in cell bodies. 5. Mobilization of Ca2+ from the IP3‐sensitive store, by bradykinin exposure, was found to be independent of the caffeine‐sensitive pool. There was no apparent ‘cross‐talk’ between both Ca2+ pools. 6. We conclude that changes in [Ca2+]i in cell bodies depend on both membrane Ca2+ channels and intracellular Ca2+ stores. During NGF‐induced differentiation there is a predominance of N‐type Ca2+ channels in growth cones, while Ca2+ stores are of minor importance in these structures.
Monitoring and handling of actuator faults in a distributed model predictive control system

In this work, we focus on monitoring and handling of actuator faults in a distributed model predictive control (DMPC) system to maintain operation at a desired steady state in the presence of control actuator faults. A model-based fault detection (FD) system is designed which detects the actuator faults in the closed-loop system and suitable strategies are devised for how to reconfigure the algorithms in the DMPC system to account for the faults and maintain stability of the closed-loop system. A chemical process example, consisting of two continuous stirred tank reactors (CSTR) and a flash tank separator with a recycle stream, is used to demonstrate the approach.
An Efficient Deep Neural Architecture for Multilingual Sentiment Analysis in Twitter

Sentiment analysis of tweets is often monolingual and the models provided by machine learning classifiers are usually not applicable across distinct languages. Cross-language sentiment classification usually relies on machine translation strategies in which a source language is translated to the desired target language. Machine translation is costly and the provided results are limited by the quality of the translation that is performed. In this paper, we propose an efficient translation-free deep neural architecture for performing multilingual sentiment analysis of tweets. Our proposed approach benefits from a cost-effective character-based embedding and from optimized convolutions to learn from multiple distinct languages. The resulting model is capable of learning latent features from all languages used during training at once and it does not require any translation process to be performed whatsoever. We empirically evaluate the efficiency and effectiveness of the proposed approach in tweet corpora from four different languages and we show that it presents the best trade-off among four distinct state-of-the-art deep neural architectures for sentiment analysis.
A database ontology for signal transduction pathways

Ontologies are one of the key technologies for data integration and meta-databases, by connecting databases at a semantical level. Still, the database has to be connected to the ontology and vice versa. To achieve this, we propose a two step process. First, we automatically generate an ontology directly from the database schema. Next, we annotate this with concepts from a domain specific ontology. We demonstrate this for signal transduction pathways, which describe how cells can react to external stimuli. In this paper we present our mapping of database schemas to ontologies and describe how these ontologies can be enriched by semantical information.
Multiplexed quantification of human IgG, IgA, and IgM with the FlowMetrix system.

A quantitative assay for the three major serum immunoglobulins (Igs) has been developed for the FlowMetrixTM system that performs each measurement simultaneously in the same test tube. The FlowMetrix system is a computer-enhanced flow cytometer that utilizes multiple fluorescent color sets of microspheres to provide a multiplexed format (1)(2). The microspheres are 5.5 μm in diameter and are composed of polystyrene and methacrylate to provide a surface carboxylate functionality. They are dyed internally with a mixture of two fluorophores that enables their classification into 64 distinct color sets. Igs are found in serum at high concentrations, allowing their assay in the competitive inhibition format. Each assay was developed by the attachment of purified IgG, IgA, or IgM to three of the available 64 uniquely fluorescing microsphere sets. Antibody specifically reactive to each Ig class was then labeled with a third fluorophore that acted as the reporter molecule. The amount of this reporter detected on the microsphere surface was inversely proportional to the concentration of soluble Ig in the serum sample. Each assay was conveniently optimized by altering the concentration of reporter antibody to provide a dynamic range encompassing the …
forsingle-nucleotide resolution reveals widespread regulatory roles A systematic study of gene expression variation at Material Supplemental

Material Supplemental http://genome.cshlp. org/content/suppl/2012/03/15/gr.117366. 110.DC1. html References http://genome.cshlp. org/content/22/6/1089.full. html#ref-list-1 This article cites 34 articles, 15 of which can be accessed free at: License Commons Creative . http://creativecommons.org/licenses/by-nc/3.0/ described at as a Creative Commons License (Attribution-NonCommercial 3.0 Unported License), ). After six months, it is available under http://genome.cshlp. org/site/misc/terms.xhtml for the first six months after the full-issue publication date (see This article is distributed exclusively by Cold Spring Harbor Laboratory Press