Miracle-dz/UniFAR-FTUs huggingface dataset:
Myelin‐, reactive glia‐, and scar‐derived CNS axon growth inhibitors: Expression, receptor signaling, and correlation with axon regeneration

Axon regeneration is arrested in the injured central nervous system (CNS) by axon growth‐inhibitory ligands expressed in oligodendrocytes/myelin, NG2‐glia, and reactive astrocytes in the lesion and degenerating tracts, and by fibroblasts in scar tissue. Growth cone receptors (Rc) bind inhibitory ligands, activating a Rho‐family GTPase intracellular signaling pathway that disrupts the actin cytoskeleton inducing growth cone collapse/repulsion. The known inhibitory ligands include the chondroitin sulfate proteoglycans (CSPG) Neurocan, Brevican, Phosphacan, Tenascin, and NG2, as either membrane‐bound or secreted molecules; Ephrins expressed on astrocyte/fibroblast membranes; the myelin/oligodendrocyte‐derived growth inhibitors Nogo, MAG, and OMgp; and membrane‐bound semaphorins (Sema) produced by meningeal fibroblasts invading the scar. No definitive CSPG Rc have been identified, although intracellular signaling through the Rho family of G‐proteins is probably common to all the inhibitory ligands. Ephrins bind to signalling Ephs. The ligand‐binding Rc for all the myelin inhibitors is NgR and requires p75NTR for transmembrane signaling. The neuropilin (NP)/plexin (Plex) Rc complex binds Sema. Strategies for promoting axon growth after CNS injury are thwarted by the plethora of inhibitory ligands and the ligand promiscuity of some of their Rc. There is also paradoxical reciprocal expression of many of the inhibitory ligands/Rc in normal and damaged neurons, and NgR expression is restricted to a limited number of neuronal populations. All these factors, together with an incomplete understanding of the normal functions of many of these molecules in the intact CNS, presently confound interpretive acumen in regenerative studies. © 2004 Wiley‐Liss, Inc.
Effect of Futures Trading on Spot Market Volatility: Evidence from Indian Commodity Derivatives Markets

This study investigates the relationship between futures trading activity and spot market volatility for agricultural, metal, precious metals and energy commodities in Indian commodity derivatives market. This article contributes to the debate whether the futures trading in Indian commodity futures market stabilizes or destabilizes spot market. We explore this issue by modeling contemporaneous as well as dynamic relationship between spot volatility and futures trading activity including trading volume (speculative/day trading) and open interest (hedging). Following Bessembinder and Senguin (1992), we examine contemporaneous relationship through augmented GARCH model in which spot volatility is modeled as GARCH (1,1) process and trading activity is used as explanatory variable. We also decompose futures trading volume and open interest series into expected and unexpected component. The lead-lag relationship between spot price volatility and futures trading volume and open interest is investigated through VAR model. Granger causality tests, forecast error variance decompositions and impulse response function are used to understand the dynamic relationship between these variables. We found that both expected and unexpected futures trading volume affects contemporaneous spot volatility positively. However, in case of agricultural commodities only unexpected volume affects the contemporaneous spot volatility. Granger causality tests, forecast error variance decompositions and impulse response function confirm that the lagged unexpected volatility causes spot price volatility for all commodities. The effect of speculative/day trading activity measured by trading volume on spot market volatility is positive. However, hedging activity measured by open interest does not show significant effect on spot market volatility. We do not find any effect of spot volatility on futures trading activity for most of the commodities.
Involvement of the gp130 cytokine transducer in MtT/S pituitary somatotroph tumour development in an autocrine-paracrine model.

OBJECTIVE gp130 cytokines are placed as auto-paracrine regulators of pituitary function, since they, as well as their receptors, have been shown to be expressed in and to act in normal and tumoral anterior pituitary cells. The objective of this work was to study their involvement in a model that shows the interaction between different cellular types that participate in a tumorigenic process. DESIGN The dependence of a pituitary somatotrophic cell line (MtT/S) on a gp130 cytokine-producing folliculostellate (FS) cell line (TtT/GF) for tumorigenesis in vivo has been described. In order to study the participation of gp130 cytokines in the auto-paracrine stimulation of MtT/S growth, we generated MtT/S gp130 sense (gp130-S) and gp130 antisense (gp130-AS) clones stably transfected with pcDNA3/gp130 sense and pcDNA3/gp130 antisense vectors respectively. METHODS AND RESULTS Functional characterization studies revealed that gp130-AS clones have an inhibited gp130 signalling, and proliferation studies showed that they have an impaired response to gp130 cytokines but respond normally to other independent stimuli. When injected into nude mice, MtT/S clones respond differently depending on cell number; at high concentrations MtT/S clones alone generated tumours equivalent in size to tumours derived from MtT/S plus TtT/GF cells. At low concentrations, MtT/S sense and control clones generated tumours of smaller size than tumours derived from these same clones plus TtT/GF cells, showing a dependence on FS cells. In both cases MtT/S gp130-AS clones had impaired tumour development. Furthermore, vessel density was significantly lower in tumours derived from gp130-AS plus TtT/GF cells. CONCLUSIONS This study underlines the importance of gp130 cytokines in proliferation and establishes its role in auto-paracrine pituitary growth regulation.
Clusterers: a comparison of partitioning and density-based algorithms and a discussion of optimisations

Though data mining is a relatively recent innovation, the improvements it offers over traditional data analysis have seen the field expand rapidly. Given the critical requirement for the efficient and accurate delivery of useful information in today's data-rich climate, significant research in the topic continues. Clustering is one of the fundamental techniques adopted by data mining tools across a range of applications. It provides several algorithms that can assess large data sets based on specific parameters and group related data points. This paper compares two widely used clustering algorithms, K-Medoids and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), against other well-known techniques. The initial testing conducted on each technique utilises the standard implementation of each algorithm. Further experimental work proposes and tests potential improvements to these methods, and presents the UltraK-Medoids and UltraDBScan algorithms. Various key applications of clustering methods are detailed, and several areas of future work have been suggested.
Testing static tradeoff against pecking order models of capital structure 1

This paper tests traditional capital structure models against the alternative of a pecking order model of corporate financing. The basic pecking order model, which predicts external debt financing driven by the internal financial deficit, has much greater timeseries explanatory power than a static tradeoff model, which predicts that each firm adjusts gradually toward an optimal debt ratio. We show that our tests have the power to reject the pecking order against alternative tradeoff hypotheses. The statistical power of some usual tests of the tradeoff model is virtually nil. ( 1999 Elsevier Science S.A. All rights reserved. JEL classification: G32
Enhancing accessibility: Mobile to ATM case study

People with disabilities encounter daily many barriers that prevent them to interact with electronic devices in their surroundings. The INREDIS project has designed a cloud based platform to overcome these challenges by turning mobile devices into personalized and universal remote controls. In more detail, the INREDIS platform is capable of identifying the user needs, personalizing the mobile phone interface to enable multimodal HCI and interacting with the target device. In this paper we describe the design, implementation and evaluation with real users of this accessibility platform in a banking environment. The developed prototypes depicted in this paper provide multimodal interfaces for people with visual and motor difficulties so they can execute some banking services at an ATM by interacting with their smartphone or computer. Tests results and optimistic user's feedback confirm that the use of a mobile device could enable a more secure and accessible mode to interact with indoor and outdoor devices.
Comparing Techniques for Mobile Interaction with Objects from the Real World.

Mobile interaction with objects from the real world is gaining in popularity and importance as different mobile technologies increasingly provide the basis for the extraction and usage of information from physical objects. So far, Physical Mobile Interaction is used in rather simple ways. This paper presents a comparison and evaluation of more complex and sophisticated techniques for Physical Mobile Interaction. The results indicate the importance of usability guidelines that pay attention to these new interaction techniques.
Nephrectomy Type Was Not Associated with a Subsequent Risk of Coronary Heart Disease: A Population-Based Study

Previous studies investigated the impacts of a partial nephrectomy (PN) or radical nephrectomy (RN) on cardiovascular events and death. However, the association between the type of nephrectomy (PN vs. RN) and cardiovascular disease is still equivocal. This retrospective cohort study aimed to compare the risk of coronary heart disease (CHD) between patients who underwent a PN and those who underwent an RN. We used data from the Taiwan Longitudinal Health Insurance Database 2005. In total, 60 patients who underwent a PN and 545 patients who underwent an RN were included. Each patient was tracked for 1-, 2-, 3-, and 5-year periods to identify those who were subsequently diagnosed with CHD. Cox proportional hazard regression analyses were used to calculate hazard ratios (HRs) for CHD during 1-, 2-, 3-, and 5-year follow-up periods between these two cohorts. For the 1-year follow-up period, the adjusted HR was 0.39 (95% CI: 0.05~2.90, p = 0.355) for patients who underwent a PN compared to those who underwent an RN. Additionally, the adjusted HRs of CHD in patients who underwent a PN for 2-, 3- and 5-year follow-up periods were 1.40 (95% CI: 0.62~3.16, p = 0.417), 1.09 (95% CI: 0.52~2.31, p = 0.814), and 1.02 (95% CI: 0.48~2.18, p = 0.961), respectively, compared to those who underwent an RN. We concluded that there was no significant difference in the risk of CHD between patients who underwent a PN and those who underwent an RN.
New paradigm of learnable computer vision algorithms based on the representational MDL principle

Learning is one of the most crucial components, which increases generality, flexibility, and robustness of computer vision systems. At present, image analysis algorithms adopt particular machine learning methods resulting in rather superficial learning. We present a new paradigm for constructing essentially learnable image analysis algorithms. Learning is interpreted as optimization of image representations. Notion of representation is formalized within information-theoretic framework. Optimization criterion is derived from well-known minimum description length (MDL) principle. Adaptation of the MDL principle in computer vision has been receiving increasing attention. However, this principle has been applied in heuristic way. We deduced representational MDL (RMDL) principle that fills the gap between theoretical MDL principle and its practical applications. The RMDL principle gives criteria both for optimal model selection of a single image within given representation, and for optimal representation selection for an image sample. Thus, it can be used for optimization of computer vision systems functioning within specific environment. Adequacy of the RMDL principle was validated on segmentation-based representations applied to different object domains. A method for learning local features as representation optimization was also developed. This method outperformed some popular methods with predefined representations such as SURF. Thus, the paradigm can be admitted as promising.
Optimal Capital Structure with Endogenous Default and Volatility Risk

This paper analyzes the capital structure of a firm in an infinite time horizon following Leland (1994) under the more general hypothesis that the firm’s assets value process belongs to a fairly large class of stochastic volatility models. By applying singular perturbation theory, we fully describe the (approximate) capital structure of the firm in closed form as a corrected version of Leland (1994) and analyze the stochastic volatility effect on all financial variables. We propose a corrected version of the smooth-fit principle under volatility risk useful to determine the optimal stopping problem solution (i.e. endogenous failure level) and a corrected version for the Laplace transform of the stopping failure time. The numerical analysis obtained from exploiting optimal capital structure shows enhanced spreads and lower leverage ratios w.r. t. Leland (1994), improving results in a robust model-independent way.
Auto-inhibition of rat parallel fibre–Purkinje cell synapses by activity-dependent adenosine release

Adenosine is an important signalling molecule involved in a large number of physiological functions. In the brain these processes are as diverse as sleep, memory, locomotion and neuroprotection during episodes of ischaemia and hypoxia. Although the actions of adenosine, through cell surface G‐protein‐coupled receptors, are well characterized, in many cases the sources of adenosine and mechanisms of release have not been defined. Here we demonstrate the activity‐dependent release of adenosine in the cerebellum using a combination of electrophysiology and biosensors. Short trains of electrical stimuli delivered to the molecular layer in vitro, release adenosine via a process that is both TTX and Ca2+ sensitive. As ATP release cannot be detected, adenosine must either be released directly or rapidly produced by highly localized and efficient extracellular ATP breakdown. Since adenosine release can be modulated by receptors that act on parallel fibre–Purkinje cell synapses, we suggest that the parallel fibres release adenosine. This activity‐dependent adenosine release exerts feedback inhibition of parallel fibre–Purkinje cell transmission. Spike‐mediated adenosine release from parallel fibres will thus powerfully regulate cerebellar circuit output.
Utilizing contextual information for mobile communication

Mobile phones enable us to be reachable by phone calls anywhere and anytime. However, it is not always appropriate to answer a phone call. Even a ringing or vibrating phone can be inappropriate in some situations. The information required to assess if a call is appropriate is split between the caller and the callee. Only the caller knows the importance of the call and only the callee knows her context. Sharing parts of this context with the potential caller would enable the caller to make a better decision. Based on previous work we conducted a survey to learn about the contextual information that users believe to be important for this decision. We derive context information that users will to share and consider relevant and helpful. Further, we present a mobile application that augments users' address book with contextual information that we aim to study in the large.
The Influence of Stress on Body Mass Index among Female University Students

Background: The interrelatedness between obesity and psychological problems seems to be twofold, in that clinically meaningful psychological distress might foster weight gain and obesity may lead to psychosocial problems. Stress may contribute to changes in dietary behaviors that lead to weight change, with various effects related to sex baseline body mass index, or cortisol reactivity in response to stress. Objective: To describe the relationship between stress, weight-related health behaviors (e.g., eating behaviors, physical activity, sedentary behavior, sleep, cigarette smoking and binge drinking), and weight status using cross-sectional data from community college students. Methods: This was a community-based cross-sectional study. Data were collected from representative sample of undergraduate female students in Kingdom of Saudi Arabia. A total of 208 undergraduate female students were included in this study. The study period was from October 2017 to December 2017. Data were collected by means of personal interview with the participants using a predesigned questionnaire which was distributed among students and filled by personal interviewing after a brief introduction or explanation of the idea of the research to the participants . Results: There was a high significant correlation between stress and BW (P= 0.004). We found no relation between BW and academic year, fast food consumption, main meal content, muscular exercise and cause of stress. There was a high significant correlation between BW and number of meals per day (P= 0.000), stress level (P=0.000) and dealing with stress (P=0.017). Conclusion and Recommendations: Factors which were significantly associated with BMI and stress should be further studied to include number of meals per day, stress level and dealing with stress). Interventions among university students should relate actual measured BMI to stress perception of the students in order to target students at risk. Universities should offer individual counselling for at risk students in order to prevent eating disorders, and should offer psychological and stress related counselling, but should also counteract unrealistic body image concerns of students by broad health communication campaigns.
Inhibition of Inflammatory Response by Artepillin C in Activated RAW264.7 Macrophages

Artepillin C (3,5-diprenyl-4-hydroxycinnamic acid) is the main bioactive component of Brazilian green propolis. The aim of this study was to investigate the anti-inflammatory effect of artepillin C on LPS + IFN-γ- or PMA-stimulated RAW264.7 macrophages. The cell viability was evaluated by MTT and LDH assays. The radical scavenging ability was determined using DPPH• and ABTS•+. ROS and RNS generation was analyzed by chemiluminescence. NO concentration was detected by the Griess reaction. The release of various cytokines by activated RAW264.7 cells was measured in the culture supernatants using a multiplex bead array system based on xMAP technology. NF-κB activity was confirmed by the ELISA-based TransAM NF-κB kit. At the tested concentrations, the compound did not decrease the cell viability and did not cause the cytotoxicity. Artepillin C exerted strong antioxidant activity, significantly inhibited the production of ROS, RNS, NO, and cytokine IL-1β, IL-3, IL-4, IL-5, IL-9, IL-12p40, IL-13, IL-17, TNF-α, G-CSF, GM-CSF, MCP-1, MIP-1α, MIP-1β, RANTES, and KC, and markedly blocked NF-κB expression in stimulated RAW264.7 macrophages. Our findings provide new insights for understanding the mechanism involved in the anti-inflammatory effect of artepillin C and support the application of Brazilian green propolis in complementary and alternative medicine.
Surface phenotypic characteristics and virulence of Spanish isolates of Aeromonas salmonicida after passage through fish

Eleven strains of Aeromonas salmonicida were passaged twice by intraperitoneal injection through rainbow trout and reisolated from the kidney of moribund fish. The surface characteristics and virulence of the strains changed following passage through fish. None of the in vitro tests used could effectively predict the in vivo virulence.
Fixed-lag particle filter for continuous context discovery using Indian Buffet Process

Exploiting context from stream data in pervasive environments remains a challenge. We aim to extract proximal context from Bluetooth stream data, using an incremental, Bayesian nonparametric framework that estimates the number of contexts automatically. Unlike current approaches that can only provide final proximal grouping, our method provides proximal grouping and membership of users over time. Additionally, it provides an efficient online inference. We construct co-location matrix over time using Bluetooth data. A Poisson-exponential model is used to factorize this matrix into a factor matrix, interpreted as proximal groups, and a coefficient matrix that indicates factor usage. The coefficient matrix follows the Indian Buffet Process prior, which estimates the number of factors automatically. The non-negativity and sparsity of factors are enforced by using the exponential distribution to generate the factors. We propose a fixed-lag particle filter algorithm to process data incrementally. We compare the incremental inference (particle filter) with full batch inference (Gibbs sampling) in terms of normalized factorization error and execution time. The normalized error obtained through our incremental inference is comparable to that of full batch inference, whilst the execution time is more than 100 times faster. The discovered factors have similar meaning to the results of the popular Louvain method for community detection.
What isn’t an NTFP?

At every meeting where NTFPs arediscussed there will be some discussion about theterminology and about what should be included and whatshould not be included in the definition. There are manyalternate terms that are used more or less as synonyms,each with its proponents. Terms such as ‘wild products’,‘natural products’, ‘non-timber forest and grasslandproducts’, ‘veld products’ and ‘sustainably produced woodproducts’ (ostensibly distinct from industrial timber) andmany others have entered the vernacular.While in some ways this interminable debate can appeartrivial, the fact is that it reflects ambiguity and confusionthat inhibits understanding and progress in research anddevelopment. There are major differences in theunderstanding of what an NTFP is and, more importantly,in the expectations of how and why NTFPs are important.Different individuals/organisations use the same term, buthave modified the definition in different ways to suit theirneeds. The term and the underlying concepts have differentmeanings to different people, so both agreements anddisagreements can be false. On the positive side, thisambiguity has made it possible to bring together ideasabout rural development and conservation that mightotherwise have seemed incompatible. However, similaritiesin the terms often disguise real differences in understandingand in assumptions, values and beliefs. There is a risk thatthe ‘NTFP concept’ will be seen to have failed if it doesnot meet the unattainable expectations that have been raisedbecause of improper or inconsistent interpretation.In this paper I analyse the elements of the terminologyby looking at the underlying assumptions and beliefs of