Miracle-dz/UniFAR-FTUs huggingface dataset:
Peptidergic modulation of neuronal circuitry controlling feeding in Aplysia

We examined the effects of 3 neuropeptides and the bioactive amine 5-HT on identified motoneurons (B15 and B16) and interneurons (B4, B5) involved in the control of feeding behavior in Aplysia californica. The application of egg-laying hormone (ELH), small cardioactive peptide b (SCPb), and 5-HT elicits distinct patterns of synaptically induced bursting in the neurons, while PheMetArgPheamide (FMRFamide) inhibits firing due to synaptic activity. Repetitive IPSPs recorded in B15 and B16 are induced by 5-HT and SCPb and inhibited by FMRFamide. The substances also may act directly: In solutions that block synaptic transmission SCPb excites B15, ELH excites B16, 5-HT excites B15, B16, and B4, and FMRFamide both inhibits B15 and B16 and excites B4. We suggest that the output of a buccal ganglion central pattern generator may be modulated to produce distinct patterns of motoneuron activity by these candidate transmitters. We also noted differences in the intrinsic properties of the 2 motoneurons. B15 contains SCPb immunoreactivity while B16 does not. This finding suggests that B15 may be the source for the SCPb immunoreactivity previously found at the ARC muscle and that SCPb may be acting in an autocrine mode. Also, B15 has a significantly lower resting potential than B16 and contains a large transient outward (Ia-like) current. The candidate transmitters act by exciting or inhibiting elements at every level within the hierarchically organized motor system that controls feeding. This expands the diversity of behavioral repertoires that may be elicited from a particular neural circuit.
Evaluation Model Based on Support Vector Machine for Community Micro-Blog Influence

As a widely used medium platform, Micro-blog influence research is a hotspot. The community micro-blog, which is used as an effective tool by social managers in virtual community, has developed rapidly in recent years. As the basis of government micro-blog system in China, the community blog influence has great importance to guide the public popular feelings and guarantee the safety of the virtual social network. The article focuses on the evaluation methods of the community micro-blog influence. Firstly, an index system is presented, both quantitative index and qualitative index are considered based on the mechanism of information dissemination of micro-blog, Then, principal component analysis (PCA) is used to compose these indexes into some comprehensive indexes to simplify the index system, finally, support vector machine (SVM) is adopted for the evaluation model. Practical examples show that the model established in this paper outperforms others in evaluation accuracy.
Classifying Cytochrome c Oxidase subunit 1 by translation initiation mechanism using side effect machines

Cytochrome c oxidase subunit 1 (cox1) is unusual among mitochondrial genes in that instead of using AUG or one of the recognized alternative start codons it often appears to use an unknown means for initiating translation. However, the frequency of this unusual behavior as well as the underlying molecular mechanism are unknown. In this paper we use side effect machines to probe for signal in the sequence. Evolved side effect machines were able to correctly classify cox1 genes with ambiguous start codons 80.1% of the time. Side effect machines are finite state machines that have side effects associated with their states. In this study a simple side effect, a counter for the number of times the state was entered, is used. The problem is found to be challenging, a substantial majority of replicates found no signal, but some classifiers with statistically significant classification ability were located.
Analysis of the Phlebiopsis gigantea Genome, Transcriptome and Secretome Provides Insight into Its Pioneer Colonization Strategies of Wood

Collectively classified as white-rot fungi, certain basidiomycetes efficiently degrade the major structural polymers of wood cell walls. A small subset of these Agaricomycetes, exemplified by Phlebiopsis gigantea, is capable of colonizing freshly exposed conifer sapwood despite its high content of extractives, which retards the establishment of other fungal species. The mechanism(s) by which P. gigantea tolerates and metabolizes resinous compounds have not been explored. Here, we report the annotated P. gigantea genome and compare profiles of its transcriptome and secretome when cultured on fresh-cut versus solvent-extracted loblolly pine wood. The P. gigantea genome contains a conventional repertoire of hydrolase genes involved in cellulose/hemicellulose degradation, whose patterns of expression were relatively unperturbed by the absence of extractives. The expression of genes typically ascribed to lignin degradation was also largely unaffected. In contrast, genes likely involved in the transformation and detoxification of wood extractives were highly induced in its presence. Their products included an ABC transporter, lipases, cytochrome P450s, glutathione S-transferase and aldehyde dehydrogenase. Other regulated genes of unknown function and several constitutively expressed genes are also likely involved in P. gigantea's extractives metabolism. These results contribute to our fundamental understanding of pioneer colonization of conifer wood and provide insight into the diverse chemistries employed by fungi in carbon cycling processes.
Therapeutic Action of Fluoxetine is Associated with a Reduction in Prefrontal Cortical miR-1971 Expression Levels in a Mouse Model of Posttraumatic Stress Disorder

MicroRNAs (miRNA) are a class of small non-coding RNAs that have recently emerged as epigenetic modulators of gene expression in psychiatric diseases like schizophrenia and major depression. So far, miRNAs have neither been studied in patients suffering from posttraumatic stress disorder (PTSD) nor in PTSD animal models. Here, we present the first study exploring the connection between miRNAs and PTSD. Employing our previously established PTSD mouse model, we assessed miRNA profiles in prefrontal cortices (PFCs) dissected from either fluoxetine or control-treated wildtype C57BL/6N mice 74 days after their subjection to either a single traumatic electric footshock or mock-treatment. Fluoxetine is an antidepressant known to be effective both in PTSD patients and in mice suffering from a PTSD-like syndrome. Screening for differences in the relative expression levels of all potential miRNA target sequences of miRBase 18.0 by pairwise comparison of the PFC miRNA profiles of the four mouse groups mentioned resulted in identification of five miRNA candidate molecules. Validation of these miRNA candidates by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) revealed that the therapeutic action of fluoxetine in shocked mice is associated with a significant reduction in mmu-miR-1971 expression. Furthermore, our findings suggest that traumatic stress and fluoxetine interact to cause distinct alterations in the mouse PFC miRNA signature in the long-term.
Optimal power allocation for pilot-assisted interference alignment in MIMO interference networks: Test-bed results

This paper addresses channel training and data communication over multi-input multi-input (MIMO) interference networks. We consider a pilot-assisted interference alignment scheme in which part of radio resources are allocated to channel training and the remaining resources are used for data transmission. A more accurate channel estimation can be obtained by increasing pilot transmission power. Since each transmitter has limited energy budget, this implies that less power is available for data transmission. Clearly, there is a trade off between the allocated power for channel training and the one for data communication. In order to investigate this trade off, first we compute an achievable sum-rate, and next we find the optimum power allocation to pilot transmission and data transmission. Finally, we verify these theoretical results with experimental measurements on USRP-based test-bed.
A Task Assignment Algorithm for Multiple Aerial Vehicles to Attack Targets With Dynamic Values

A good task assignment is an important guarantee to achieve great combat effectiveness. This paper investigates the task assignment problem, where the value of the targets is time changing in the battlefield, and presents a solution approach that is a combination of two algorithms: the multidestination route planning algorithm based on dynamic programming and the multisubgroup ant colony algorithm (MSACO). The two algorithms coordinately solve the task assignment problem. The route planning algorithm can obtain available routes between any two targets and provide reasonable routing information for MSACO. Then, the ant colony algorithm is applied to solve the task assignment problem. To solve the task assignment problem in the battlefield environment, several key technologies are introduced to improve the traditional ant colony algorithm, which include the subgroup selection strategy, the dynamic candidate aggregate policy, the state transferring policy, and the information-element updating mechanism. Simulation results show that the proposed approach can produce a reasonable and available plan for all the test cases in short computational time.
M-Hadith: Retrieving Malay Haditli text in a mobile application

Recent rapid advances in handheld devices make it possible for users to retrieve information anytime and anywhere. Existing information retrieval techniques usually require the users to spend much effort to refine their queries. Information retrieval in mobile devices would represent an extremely challenging search environment. Due to the existing challenging constraints in technology, there is a need to have a simple and easy information retrieval in mobile with an attractive interface to attract more users to use this application. The M-Hadith prototype is designed to provide searching Malay Hadith text based on query word using stemming algorithm to get results on the query. Since, stemming is a basic text processing tool where it is used for efficient and effective text retrieval and machine translation, therefore, it has been adapted in the development of M-Hadith. Early results in the mobile simulator show compatibility and efficiency in various type of mobile devices.
Visual aesthetic quality assessment with a regression model

Aesthetic image analysis has drawn much attention in recent years. However, assessing the aesthetic quality especially aesthetic score prediction is a challenging problem. In this paper, we interpret aesthetic quality assessment as a regression problem and present a new framework by directly training a regression model using a neural network. Firstly, to extract the aesthetic features which are difficult to design manually, we utilize the convolutional network to learn the features. Then, a regression model is trained based on the aesthetic features. Different from classification models which can only predict aesthetic class (high or low) in most existing works, the regression model can predict continuous aesthetic score. Experimental results on a recently published large-scale dataset show that the proposed method can assess the degree of aesthetic quality similar to human visual system effectively and outperforms the state-of-the-art methods.
Deviation maps: enhancing robustness and predictability of indoor positioning systems

Many indoor positioning methods and systems exhibit high inaccuracies and structural positioning biases, when deployed and evaluated in real-world environments. This holds especially for signal-strength-based positioning, the prevalent means for position tracking in environments, that are not suitable for GNSS positioning, such as large building complexes. In such environments though strong positioning inaccuracies and biases result from the many building elements with different attenuation properties. We propose and evaluate deviation maps as a means for capturing, and thereby reducing, positioning errors and biases as prevalent in different parts of deployment's building complex.
Estimating dynamic macroeconomic models: how informative are the data?

Central banks have long used dynamic stochastic general equilibrium models, which are typically estimated by using Bayesian techniques, to inform key policy decisions. This paper offers an empirical strategy that quantifies the information content of the data relative to that of the prior distribution. Using an off‐the‐shelf dynamic stochastic general equilibrium model applied to quarterly euro area data from 1970, quarter 3, to 2009, quarter 4, we show how Monte Carlo simulations can reveal parameters for which the model's structure obscures identification. By integrating out components of the likelihood function and conducting a Bayesian sensitivity analysis, we uncover parameters that are weakly informed by the data. The weak identification of some key structural parameters in our comparatively simple model should raise a red flag to researchers trying to draw valid inferences from, and to base policy on, complex large‐scale models featuring many parameters.
Full Reversal of Alzheimer's Disease-Like Phenotype in a Mouse Model with Conditional Overexpression of Glycogen Synthase Kinase-3

Glycogen synthase kinase-3 (GSK-3) is a ubiquitously expressed serine/threonine kinase that is particularly abundant in the CNS. Dysregulation of GSK-3 activity is believed to play a key role in the pathogenesis of CNS chronic disorders such as Alzheimer's disease (AD), bipolar disorder, and Huntington's disease, and of metabolic disorders such as type II diabetes. Accordingly, GSK-3 inhibitors have been postulated as therapeutic tools for these diseases. Interestingly, pathophysiological and pharmacological regulation of GSK-3 is affected by an amplification mechanism that applies both to inhibition and activation. The possibility therefore exists that sustained inhibition or activation might persist after cessation of the initial trigger. Regarding AD, GSK-3 has been shown to accumulate in pretangle neurons. Furthermore, GSK-3 phosphorylates tau in most serine and threonine residues hyperphosphorylated in PHF (paired helical filament)-tau and GSK-3 activity contributes both to β-amyloid production and to β-amyloid-mediated neuronal death. In good agreement, mice with conditional overexpression of GSK-3 in forebrain neurons (Tet/GSK-3β mice) recapitulate aspects of AD neuropathology such as tau hyperphosphorylation, apoptotic neuronal death, and reactive astrocytosis as well as spatial learning deficit. Here, we exploit the conditional system used to generate Tet/GSK-3β mice to explore whether the biochemical, histopathological, and behavioral consequences of increased GSK-3 activity are susceptible to revert after restoration of normal GSK-3 levels. Here, we show that transgene shutdown in symptomatic mice leads to normal GSK-3 activity, normal phospho-tau levels, diminished neuronal death, and suppression of the cognitive deficit, thus further supporting the potential of GSK-3 inhibitors for AD therapeutics.
A subthreshold CMOS implementation of a two-dimensional mechanical cochlear model

We present a two-dimensional passive silicon cochlea based on the work of Watts [1993]. The model propagates waves in the backward and forward directions with succeeding stages loading earlier stages. CMOS resistors operating in the subthreshold ohmic region implement the uniform cochlear fluid. SPICE simulations reveal a cutoff slope in excess of 100 dB/oct, which compares well with experimental results.
A formal approach for the inference plane supporting integrated management tasks in the Future Internet

Integrated management of the Future Internet governs resources, networks, systems and services. This requires systems supporting services to orchestrate decision-making and management tasks. Management tasks must be performed considering end-user and network activity, and be able to enforce and verify operations for network and end-user requirements control. This paper proposes the semantic enrichment of management information described in information and data models with ontological data and provides an approach to formalize the Inference Plane promoting integrated management. The proposed semantic enrichment provides new semantic tools to integrate context information with management service operations, and offers a more complete understanding and hence, a more inclusive governance of the management of resources, devices, networks, systems and services. The semantic approach consists of the ontology for support and management, which provide the necessary semantic richness to represent the different types of information needed to be integrated in management operations. In particular, it can be used with other tools for governing and orchestrating behavior.
Arrangements of cellular complexes

In this paper we introduce a novel algorithm to combine two or more cellular complexes, providing a minimal fragmentation of the cells of the resulting complex. This algorithm has several important applications, including Boolean operations over big geometric data, like the detailed geometric modeling of buildings, the combination of 3D meshes, or the repair of graphical models. The algorithm operates over the LAR representation of argument complexes, based on sparse matrices, so being well-suited for implementation on last generation accelerators and GPGPU applications
Enhancing Heat Tolerance of the Little Dogwood Cornus canadensis L. f. with Introduction of a Superoxide Reductase Gene from the Hyperthermophilic Archaeon Pyrococcus furiosus

Production of reactive oxygen species (ROS) can be accelerated under various biotic and abiotic stresses causing lipid peroxidation, protein degradation, enzyme inactivation, and DNA damage. Superoxide reductase (SOR) is a novel antioxidant enzyme from Pyrococcus furiosus and is employed by this anaerobic hyperthermophilic archaeon for efficient detoxification of ROS. In this study, SOR was introduced into a flowering plant Cornus canadensis to enhance its heat tolerance and reduce heat induced damage. A fusion construct of the SOR gene and Green Fluorescent Protein gene (GFP) was introduced into C. canadensis using Agrobacterium-mediated transformation. Heat tolerance of the GFP-SOR expressing transgenic plants was investigated by observing morphological symptoms of heat injury and by examining changes in photosynthesis, malondialdehyde (MDA), and proline levels in the plants. Our results indicate that the expression of the P. furiosus SOR gene in the transgenic plants alleviated lipid peroxidation of cell membranes and photoinhibition of PS II, and decreased the accumulation of proline at 40°C. After a series of exposures to increasing temperatures, the SOR transgenic plants remained healthy and green whereas most of the non-transgenic plants dried up and were unable to recover. While it had previously been reported that expression of SOR in Arabidopsis enhanced heat tolerance, this is the first report of the successful demonstration of improved heat tolerance in a non-model plant resulting from the introduction of P. furiosus SOR. The study demonstrates the potential of SOR for crop improvement and that inherent limitations of plant heat tolerance can be ameliorated with P. furiosus SOR.
5G millimeter wave (mmWave) communications

5G communication system is attracting researches attention throughout the world for providing seamless user experience in 5G network which can accommodate large number of users in Internet of Things (IoT) environment with a gigabit-per-second (Gbps) data rate in mmWave communications with the consideration of Big-Data (BD). In 5G environment several billions of user devices will be connected seamlessly among each other in mmWave communications along with secure connections. 5G Millimeter Wave (mmWave) communications system proposes mmWave signal transmission along with low latency connection which will offer gigabit-per-second (Gbps) speed. This paper discusses 5G applications and services along with 5G vision and challenges. There are many challenges with the proposed mmWave communications system. 5G mmWave communications system will be revolutionizing for the users.
Integration of geospatial multi-mode transportation Systems in Kuala Lumpur

Public transportation serves people with mobility and accessibility to workplaces, health facilities, community resources, and recreational areas across the country. Development in the application of Geographical Information Systems (GIS) to transportation problems represents one of the most important areas of GIS-technology today. To show the importance of GIS network analysis, this paper highlights the determination of the optimal path between two or more destinations based on multi-mode concepts. The abstract connector is introduced in this research as an approach to integrate urban public transportation in Kuala Lumpur, Malaysia including facilities such as Light Rapid Transit (LRT), Keretapi Tanah Melayu (KTM) Komuter, Express Rail Link (ERL), KL Monorail, road driving as well as pedestrian modes into a single intelligent data model. To assist such analysis, ArcGIS's Network Analyst functions are used whereby the final output includes the total distance, total travelled time, directional maps produced to find the quickest, shortest paths, and closest facilities based on either time or distance impedance for multi-mode route analysis.
Catastrophe Bonds. From Structure to Strategy – A Cluster Analysis at European Level

As a core activity and discipline of corporate management and corporate governance, risk management is, especially nowadays, a central part in pursuing the sustainable development desiderates, both from the perspective of the firm and of the society as a whole.Considering the negative impact natural catastrophes have on the companies’ and countries’ competitiveness, the development of sustainable financial products that make a contribution to transferring the risk and allocating the capital in case of disasters stands for a continual preoccupation, especially for the (re)insurance industry, while the study of catastrophe bonds – insurance-linked securities – is of interest in the specialized literature. In this context, the scope of the present research is to expand the empirical studies within this field while examining the link between the structure of the catastrophe bonds and the risk management approach employed while accessing the capital markets through this transactions.The methodology entailed clustering a selection of transactions developed by European cedents based on the size of each issue and correlating the results with an innovative score, developed to encompass several important catastrophe bonds structural components.The findings reflect that the general structural elements of the financial transactions reflect closely the corporate approach regarding the innovative risk intermediation instruments for the examined catastrophe bonds deals. The outcomes also emphasize, as expected, that companies with a stronger presence on this market seem to have a more sophisticated risk management approach.