Miracle-dz/UniFAR-FTUs huggingface dataset:
Local Acceleration of Neurofilament Transport at Nodes of Ranvier

Myelinated axons are constricted at nodes of Ranvier. These constrictions are important physiologically because they increase the speed of saltatory nerve conduction, but they also represent potential bottlenecks for the movement of axonally transported cargoes. One type of cargo are neurofilaments, which are abundant space-filling cytoskeletal polymers that function to increase axon caliber. Neurofilaments move bidirectionally along axons, alternating between rapid movements and prolonged pauses. Strikingly, axon constriction at nodes is accompanied by a reduction in neurofilament number that can be as much as 10-fold in the largest axons. To investigate how neurofilaments navigate these constrictions, we developed a transgenic mouse strain that expresses a photoactivatable fluorescent neurofilament protein in neurons. We used the pulse-escape fluorescence photoactivation technique to analyze neurofilament transport in mature myelinated axons of tibial nerves from male and female mice of this strain ex vivo. Fluorescent neurofilaments departed the activated region more rapidly in nodes than in flanking internodes, indicating that neurofilament transport is faster in nodes. By computational modeling, we showed that this nodal acceleration can be explained largely by a local increase in the duty cycle of neurofilament transport (i.e., the proportion of the time that the neurofilaments spend moving). We propose that this transient acceleration functions to maintain a constant neurofilament flux across nodal constrictions, much as the current increases where a river narrows its banks. In this way, neurofilaments are prevented from piling up in the flanking internodes, ensuring a stable neurofilament distribution and uniform axonal morphology across these physiologically important axonal domains. SIGNIFICANCE STATEMENT Myelinated axons are constricted at nodes of Ranvier, resulting in a marked local decrease in neurofilament number. These constrictions are important physiologically because they increase the efficiency of saltatory nerve conduction, but they also represent potential bottlenecks for the axonal transport of neurofilaments, which move along axons in a rapid intermittent manner. Imaging of neurofilament transport in mature myelinated axons ex vivo reveals that neurofilament polymers navigate these nodal axonal constrictions by accelerating transiently, much as the current increases where a river narrows its banks. This local acceleration is necessary to ensure a stable axonal morphology across nodal constrictions, which may explain the vulnerability of nodes of Ranvier to neurofilament accumulations in animal models of neurotoxic neuropathies and neurodegenerative diseases.
Entrepreneurship Theory: New Challenges and Future Prospects

The paper analyses the problems of contemporary entrepreneurship theory which scientists are confronting in recent years. There are arguments given in favour of a broad definition of entrepreneurship as ‘emergence of new economic activity’. The starting point of research on entrepreneurship research is the question, ‘how, why, and when do entrepreneurial firms explore and exploit entrepreneurial opportunities? ’ According to the author of this paper, it thus becomes possible to redefine the subject of the discipline, which in turn enables a sustainable development of the theory, and a refocusing on new areas such as social and institutional entrepreneurship. The paper forecasts a shift in research on entrepreneurship beyond Western societies to encompass the so-called transitional economies and emerging markets. These countries have some important contextual differences which affect the practices of entrepreneurship and these are discussed here. Contextual differences justify the importance of investigating new institutions and actors which might become challenging subjects of entrepreneurship theory in future. The paper also discusses the agenda of entrepreneurship research in Russia, explains the reasons for the relatively weak development of Russian entrepreneurship theory, and suggests policies to improve this situation. The author stresses the changes in methods and research design and the new possibilities and empirical data sources resulting from the latest advancements in IT and big data. In particular, more intensive research and demand for this research will likely emerge because of the increasing availability of techniques for collecting and analysing big data. The author anticipates the increasing importance of international comparative studies conducted by large project teams, and of longitudinal projects to elaborate realistic recommendations for civil society, national governments, and international organizations.
Industry 4.0-Induced Change Factors and the Role of Organizational Agility

The technological advancements in the manufacturing sector confront organizations with the convergence of industrial production and information and communication technologies. The industry is supposed to realize manufacturing of individual products while maintaining economic conditions of mass production. To react to this changing environment, government and industry initiatives have been announced worldwide. Due to international integration and export-orientation of the German economy, Industry 4.0 by the German Federal Government can be considered representative for a global phenomenon of change and disruption. A vital capability to develop in such uncertain and turbulent environments is organizational agility that is defined as the ability of firms to sense environmental change and respond readily. Although well-established consulting agencies already regard organizational agility as a key ability for Industry 4.0, no systematic scientific evidence for this assertion exists. We therefore seek to answer how organizational agility can empower manufacturing companies to manage the change induced by Industry 4.0. We conduct an extensive systematic literature review, examining Industry 4.0-induced changes categorized by change factors from literature. For each category, we examine facets of organizational agility and show how companies can manage change. We discuss our results and provide implications for research and practice.
Synchrony Between Discrete Variables : 223 Slope Estimation Using a SHME Model

11 Abstract. A defining feature of many physiological systems is their synchrony and reciprocal influence. An important challenge, however, is 12 how to measure such features. This paper presents two new approaches for identifying synchrony between the physiological signals of 13 individuals in dyads. The approaches are adaptations of two recently-developed techniques, depending on the nature of the physiological time 14 series. For respiration and thoracic impedance, signals that are measured continuously, we use Empirical Mode Decomposition to extract the low15 frequency components of a nonstationary signal, which carry the signal’s trend. We then compute the maximum cross-correlation between the 16 trends of two signals within consecutive overlapping time windows of fixed width throughout each of a number of experimental tasks, and 17 identify the proportion of large values of this measure occurring during each task. For heart rate, which is output discretely, we use a structural 18 linear model that takes into account heteroscedastic measurement error on both series. The results of this study indicate that these methods are
Depressive symptoms are associated with higher morning plasma cortisol in primary care subjects.

BACKGROUND Cortisol dysregulation has a potential role in depression. AIM AND METHODS We evaluated depressive symptoms using the Hamilton Rating Scale for Depression in 48 primary care subjects without history of previous or current depression and its association with cortisol dysregulation (morning plasma cortisol, 24-hour urinary free cortisol and cortisol metabolites). Presence of metabolic syndrome and inflammatory parameters were also assessed. RESULTS Hamilton Rating Scale for Depression correlated significantly with morning cortisol, but not with urinary free cortisol or metabolites. A significant increase in morning cortisol by Hamilton groups (asymptomatic ≤8; mild to moderate: 9-18; moderate to severe: ≥19) was observed even when adjusted by age/gender. We observed no association of depressive symptoms with metabolic or inflammatory parameters. CONCLUSION Depressive symptoms in primary care subjects not consulting for their mood are associated with higher morning plasma cortisol, but not urinary cortisol or its metabolites. These observations suggest that systemic hypercortisolism and related metabolic disorders are not observed in mild/initial states of depressive disorders.
B2C - bubble to cluster: the dot.com boom, spin-off entrepreneurship, and regional industry evolution

This article studies entrepreneurial activities emerging out of one of Germanyâ€™s most prominent dot.com firms: Intershop, a maker of e-commerce software. We show that Intershop spawned at least 30 spin-offs. The majority entered locally, giving rise to a small but growing software cluster and counteracting the job losses accompanying the parent firmâ€™s drastic downsizing after 2000. We trace the knowledge transfer from Intershop to the spin-offs and relate it to recent theorizing on the spin-off process as well as spin-off-based cluster formation. The Intershop case suggests that temporarily successful dot.coms could exert lasting effects on regional development. Length 30 pages
Modeling Ventricular Muscle Cell by the Least Parameters

Modeling the dynamics of ventricular muscle cell require models that reproduce realistic characteristics in cell. In this paper, we present a minimal model for ventricular muscle cell that is designed to reproduce important characteristics of cardiac cell, including action potential (AP) amplitudes and morphologies, excitability and all or none criteria. To generate the minimal model, first, we presented a general form of a nonlinear model with twostate variables for the cell, and then parameters of the model have been fitted by using the theories and experiments that has done on COR software. Findings show the proposed minimal model has important features for example; it is simple and is computationally efficient.
An Application of Ant Colony Optimization for Software Project Scheduling with Algorithm In Artificial Intelligence

Ant colony optimization (ACO) is a population-based metaheuristic that can be used to find approximate solutions to difficult optimization problems. In ACO, a set of software agents called artificial ants search for good solutions to a given optimization problem research into developing effective computer aided techniques for planning software projects is important and challenging for software engineering. Different from projects in other fields, software projects are people-intensive activities and their related resources are mainly human resources. Thus, an adequate model for software project planning has to deal with not only the problem of project task scheduling but also the problem of human resource allocation. But as both of these two problems are difficult. The basic idea of the EBS is to adjust the allocation of employees at events and keep the allocation unchanged at non-events. With this strategy, the proposed method enables the modelling of resource conflict and task pre-emption and preserves preserves the flexibility in human resource allocation. To solve the planning problem, an ACO algorithm is further is used.
Machine learning approaches and web-based system to the application of disease modifying therapy for sickle cell

Sickle cell disease (SCD) is a common serious genetic disease, which has a severe impact due to red blood cell (RBCs) abnormality. According to the World Health Organisation, 7 million newborn babies each year suffer either from the congenital anomaly or from an inherited disease, primarily from thalassemia and sickle cell disease. In the case of SCD, recent research has shown the beneficial effects of a drug called hydroxyurea/hydroxycarbamide in modifying the disease phenotype. The clinical management of this disease-modifying therapy is difficult and time consuming for clinical staff. This includes finding an optimal classifier that can help to solve the issues with missing values, multi-class datasets, and features selection. For the classification and discriminant analysis of SCD datasets, 7 classifiers based on machine learning models are selected representing linear and non-linear methods. After running these classifiers with a single model, the results revealed that a single classifier has provided us with effective outcomes in terms of the classification performance evaluation metric. In order to produce such an optimal outcome, this research proposed and designed combined classifiers (ensemble classifiers) among the neural network’s models, the random forest classifier, and the K-nearest neighbour classifier. In this aspect, combining the levenberg-marquardt algorithm, the voted perceptron classifier, the radial basis neural classifier, and random forest classifier obtain the highest rate of performance and accuracy. This ensemble classifier receives better results during the training set and testing set process. Recent technology advances based on smart devices have improved the medical facilities and become increasingly popular in association with real-time health monitoring and remote/personal health-care. The web-based system developed under the supervision of the haematology specialist at the Alder Hey Children’s Hospital in order to produce such an effective and useful system for both patients and clinicians. To sum up, the simulation experiment concludes that using machine learning and the web-based system platforms represents an alternative procedure that could assist healthcare professionals, particularly for the specialist nurse and junior doctor to improve the quality of care with sickle cell disorder.
Shotgun Label-free Proteomic Analyses of the Oyster Parasite Perkinsus Marinus

Perkinsus marinus is an intracellular parasitic protozoan that is responsible for serious disease epizootics in marine bivalve molluscs worldwide. Despite all available information on P. marinus genomics, more baseline data is required at the proteomic level. Our aim was to study the proteome profile of in vitro cultured P. marinus isolated from oysters Crassostrea spp. using a label-free shotgun UDMS approach. A total of 4073 non redundant proteins were identified across three biological replicates with stringent identification. Proteins specifically related to adaptive survival, cell recognition, antioxidants, regulation of apoptosis and others were detected. Important virulence factors of P. marinus were identified including serine protease and irondependent superoxide dismutase. Other proteins with involvement in several pathogens invasion strategies were rhoptries, serine-threonine kinases and protein phosphatases. Interestingly, peptides corresponding to retroviruses polyproteins were identified in all replicates. The interactomic analysis of P. marinus proteins demonstrated important cluster networks related to biological processes. In conclusion, we provide the first comprehensive proteomic profile of P. marinus that can be useful for further investigations on Perkinsus biology and virulence mechanisms. DOI : 10.14302/issn.2326-0793.jpgr-17-1571 Corresponding author: Henrique César Pereira Figueiredo, Department of Preventive Veterinary Medicine, Veterinary School, Federal University of Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte, Brazil. Phone: +55-31-34092120, Fax: +55-31-34092075, E-mail address: figueiredoh@yahoo.com Running title: Proteome of Perkinsus marinus
Evaluation of terrestrial carbon cycle models through simulations of the seasonal cycle of atmospheric CO2: First results of a model intercomparison study

Results of an intercomparison among terrestrial biogeochemical models (TBMs) are reported, in which one diagnostic and five prognostic models have been run with the same long‐term climate forcing. Monthly fields of net ecosystem production (NEP), which is the difference between net primary production (NPP) and heterotrophic respiration RH, at 0.5° resolution have been generated for the terrestrial biosphere. The monthly estimates of NEP in conjunction with seasonal CO2 flux fields generated by the seasonal Hamburg Model of the Oceanic Carbon Cycle (HAMOCC3) and fossil fuel source fields were subsequently coupled to the three‐dimensional atmospheric tracer transport model TM2 forced by observed winds. The resulting simulated seasonal signal of the atmospheric CO2 concentration extracted at the grid cells corresponding to the locations of 27 background monitoring stations of the National Oceanic and Atmospheric Administration/Climate Monitoring and Diagnostics Laboratory network is compared with measurements from these sites. The Simple Diagnostic Biosphere Model (SDBM1), which is tuned to the atmospheric CO2 concentration at five monitoring stations in the northern hemisphere, successfully reproduced the seasonal signal of CO2 at the other monitoring stations. The SDBM1 simulations confirm that the north‐south gradient in the amplitude of the atmospheric CO2 signal results from the greater northern hemisphere land area and the more pronounced seasonality of radiation and temperature in higher latitudes. In southern latitudes, ocean‐atmosphere gas exchange plays an important role in determining the seasonal signal of CO2. Most of the five prognostic models (i.e., models driven by climatic inputs) included in the intercomparison predict in the northern hemisphere a reasonably accurate seasonal cycle in terms of amplitude and, to some extent, also with respect to phase. In the tropics, however, the prognostic models generally tend to overpredict the net seasonal exchanges and stronger seasonal cycles than indicated by the diagnostic model and by observations. The differences from the observed seasonal signal of CO2 may be caused by shortcomings in the phenology algorithms of the prognostic models or by not properly considering the effects of land use and vegetation fires on CO2 fluxes between the atmosphere and terrestrial biosphere.
Photoproduction of strange mesons and hyperons on the proton

Quantumchromodynamica beschrijft de interacties tussen quarks. Bij hoge energieen is deze theorie op zijn best en kunnen er zeer precieze uitspraken worden gedaan over de krachten tussen de quarks. Bij lagere energieen treedt de complexiteit van de theorie echter sterker naar voren. Juist op dit gebied richt het onderzoek van Ralph Castelijns zich. Hij voerde hiervoor experimenten uit in de deeltjesversneller van het KVI in Groningen en de elektronenversneller van ELSA in Bonn.
CO2 response curves can be measured with a field-portable closed-loop photosynthesis system

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. CO2 response curves can be measured with a field-portable closed-loop photosynthesis system D.K. Mcdermitt, J.M. Norman, J.T. Davis, T.M. Ball, T.J. Arkebauer, J.M. Welles, S.R. Roerner
Problematic overstudying: Studyholism or study addiction?

This commentary addresses Griffiths et al. (2018)’s sixth myth about work addiction. We agree that work addiction could also be spread in the school context, although we propose that problematic overstudying may be more similar to an obsession than to an addiction toward the study. We refer to the DSM-5 diagnostic criteria related to the obsessive–compulsive disorder (OCD) and the substance-use disorder, presenting some theoretical considerations related to the similarities and differences between problematic overstudying and these two diagnoses. Finally, we focus on the obsessive–compulsive personality disorder. We conclude that problematic overstudying might better be conceptualized as an OCD-related disorder.
Fragments Of The Artwork

"Fragments of the Artwork" brings together Jean Genet's critical writings and open letters on art and aesthetic issues. This collection testifies to Genet's enormous influence on the modern theater, on the development of the novel, and on the representation of crime, sex, gender, and race. In lyrical essays and one candid interview, these works present an untutored, original, defiant Genet, displaying his provocative insights and acuities on a range of topics. Genet wrestles with the athletic genius of Rembrandt, adores the intricate criminal resurrections of Dostoevsky, challenges our easy readings of Brecht, and, in what is one of the most exalting art historical essays ever written, provides us with his detailed personal account of the work and presence of Alberto Giacometti. Altogether these essays comprise a series of engrossing meditations on the central motives of theatricality and art.
Technologies for Next-generation Wireless LANs Special Feature

This article reviews wireless local area networks (WLANs) as the most appropriate method to implement the home network services described in the previous articles. After surveying the trends for WLANs, we describe next-generation WLAN technologies including MIMO (multiple input multiple output) transmission, which uses multiple transmitting and receiving antennas. MIMO is the most attractive candidate for high-data-rate transmission and large communication capacity without expanding the signal bandwidth. We also describe various approaches to next-generation WLANs. Technologies for Next-generation Wireless LANs Special Feature † NTT Network Innovation Laboratories Yokosuka-shi, 239-0847 Japan E-mail: kagami.osamu@lab.ntt. co.jp