Miracle-dz/UniFAR-FTUs huggingface dataset:
Multimodal Modeling of Neural Network Activity: Computing LFP, ECoG, EEG, and MEG Signals With LFPy 2.0

Recordings of extracellular electrical, and later also magnetic, brain signals have been the dominant technique for measuring brain activity for decades. The interpretation of such signals is however nontrivial, as the measured signals result from both local and distant neuronal activity. In volume-conductor theory the extracellular potentials can be calculated from a distance-weighted sum of contributions from transmembrane currents of neurons. Given the same transmembrane currents, the contributions to the magnetic field recorded both inside and outside the brain can also be computed. This allows for the development of computational tools implementing forward models grounded in the biophysics underlying electrical and magnetic measurement modalities. LFPy (LFPy.readthedocs.io) incorporated a well-established scheme for predicting extracellular potentials of individual neurons with arbitrary levels of biological detail. It relies on NEURON (neuron.yale.edu) to compute transmembrane currents of multicompartment neurons which is then used in combination with an electrostatic forward model. Its functionality is now extended to allow for modeling of networks of multicompartment neurons with concurrent calculations of extracellular potentials and current dipole moments. The current dipole moments are then, in combination with suitable volume-conductor head models, used to compute non-invasive measures of neuronal activity, like scalp potentials (electroencephalographic recordings; EEG) and magnetic fields outside the head (magnetoencephalographic recordings; MEG). One such built-in head model is the four-sphere head model incorporating the different electric conductivities of brain, cerebrospinal fluid, skull and scalp. We demonstrate the new functionality of the software by constructing a network of biophysically detailed multicompartment neuron models from the Neocortical Microcircuit Collaboration (NMC) Portal (bbp.epfl.ch/nmc-portal) with corresponding statistics of connections and synapses, and compute in vivo-like extracellular potentials (local field potentials, LFP; electrocorticographical signals, ECoG) and corresponding current dipole moments. From the current dipole moments we estimate corresponding EEG and MEG signals using the four-sphere head model. We also show strong scaling performance of LFPy with different numbers of message-passing interface (MPI) processes, and for different network sizes with different density of connections. The open-source software LFPy is equally suitable for execution on laptops and in parallel on high-performance computing (HPC) facilities and is publicly available on GitHub.com.
Double Dividend Hypothesis: Can it be Validated by Carbon Taxation Swap With Payroll Taxes?

This paper is concerned with the proficiency assessment of the environmental tax reform to tackle the pollution and simultaneously decrease the tax burden of pre-existent labor taxation. In comparison with mainstream literature, we focus exclusively on the reduction of the tax distortions that affect labor demand, using the revenues generated by environmental levies. Our starting point is the double dividend hypothesis with respect to the environmental taxation. The main objective of this paper is to validate the second dividend hypothesis, hence testing the carbon taxation ability to reduce harmful effects of taxes on inputs such as labor. Following the trajectory of the double dividend hypothesis, the paper examines the potential of carbon taxation enactment accompanied by the payroll tax cuts in order to lower the efficiency costs of these pre-existent distortionary taxes. The feasibility of tax swap mechanism between environmental and payroll taxation is verified through estimating and comparing their efficiency costs. The results obtained from empirical analysis confirm that there is a high potential of swapping these taxes and implementing offsetting measures, where the efficiency costs of payroll taxation are considerably larger than of environmental taxation. Hence, we conclude that there is “enough room” for this tax swap mechanism to take place which would have a two-folded outcome – environment protection improvement and decreasing the efficiency costs of the fiscal system. Given the fact that the efficiency costs of environmental taxes are considerably lower (both in absolute and percentage values), than payroll taxation in the EU, it is possible to apply payroll tax cuts and consequently increase the ratio of environmental taxation. DOI: http://dx.doi. org/10.5755/j01.ee. 26.1. 8399
Assessing the Reliability of PCR, Microbiological and Histologic Methods inDetecting Helicobacter pylori in Gastric Biopsies

Background: Helicobacter pylori is currently recognized as one of the most common chronic bacterial infections worldwide. It is the cause of gastritis, peptic ulcer, gastric cancers and gastric malt lymphoma. Reliable methods of detecting this bacterium will help in successful eradication and/or reduction in the risk of gastric carcinoma. Methods: Upper endoscopy was performed on 80 patients referred for endoscopy and gastric biopsies taken from the antrum and tested by PCR, histology, urease, ELISA and culture using standard techniques. Results: The yield of Helicobacter pylori by different diagnostic methods in the study indicated that Urease had the highest positivity of 91.25% while culture was the least with 1.25%. PCR of 16S rRNA gene was the gold standard. Immunohistochemistry and SYBR Green had almost perfect agreement with PCR (kappa value=0.840; p<0.001, kappavalue= 0.88; p=0.001 respectively), Giemsa had a substantial agreement with PCR (kappa=0.770; p<0.001); ELISA had a fair agreement (kappa-value=0.220; p=0.002) while culture had a slight agreement (kappa-value=0.057; p=0.120). Conclusion: All the test methods used in the study had a significant agreement with PCR which was used as the gold standard except ELISA and culture.
Eating habits and nutritional status of pregnant women and the course and outcomes of pregnancy

The eating habits and nutritional status of future mothers have an important effect, not only on the course of pregnancy and the development of the foetus, but also on the health of the children during subsequent years of life. The objective of the study was the analysis of the relationship between eating habits and nutritional status of pregnant women on the course of pregnancy and pregnancy outcomes, based on a literature review. In the presented study the following are discussed: nutritional risk factors of pre-term birth, gestational diabetes, preeclampsia, low birth weight, infants born small for gestational age, as well as macrosomia and babies born large for gestational age. In the analysis, data was used concerning the consumption of individual products, groups of products, and dietary patterns, without consideration of dietary supplementation.
Baroclinic Wave Breaking and the Internal Variability of the Tropospheric Circulation

Abstract A simple model of the tropospheric circulation, based on a 10-level primitive equation model, is forced by linearly relaxing the potential temperature toward an idealized, zonally symmetric equilibrium field. The model equations are integrated in time until a statistically steady state is obtained. The local relationship between the state of the background flow, the direction of wave propagation, and subsequent wave breaking at the tropopause level is then investigated. Maps of potential vorticity (PV) on isentropic surfaces are analyzed and all four different types of wave breaking described recently by Peters and Waugh are shown to occur. It is found that cyclonic wave breaking events are usually initiated by poleward fluxes of wave activity, and anticyclonic events by equatorward fluxes. Composites are then used to show that equatorward fluxes are associated with a jet that is locally broad and weak, with relatively strong isentropic PV gradients to its equatorward flank. By contrast, poleward.
Usage of vertex detectors in the ATLAS trigger software

The challenging environment in which the Large Hadron Collider (LHC) experiments are going to operate implies a sophisticated trigger system, capable of real-time track and vertex reconstruction. In the ATLAS experiment, the first selection stage where these ingredients are available is the software-based High-Level Trigger (HLT), which reduces its 75 kHz input to∼200 Hz in two subsequent steps: the LVL2 and the Event Filter (EF) triggers. In this contribution we present algorithms for fast reconstruction of charged tracks in the HLT framework, including common extrapolation and fitting tools. Their application to different trigger selections and in particular to b-jet selections, used to improve the flexibility of the trigger scheme and extend its physics performance, is also discussed. Examples of performance of the presented algorithms on simulation and cosmic-ray data are given. Efficient and robust tracking capabilities are demonstrated to be achievable with average execution times well within the trigger requirements.
Application of Microfluidics in Stem Cell Culture

In this chapter, we review the recent developments, including our studies on the micro‐ fabricated devices applicable to stem cell culture. We will focus on the application of plu‐ ripotent stem cells including embryonic stem cells and induced pluripotent stem cells. In the first section, we provide a background on microfluidic devices, including their fabri‐ cation technology, characteristics, and the advantages of their application in stem cell cul‐ ture. The second section outlines the use of micropatterning technology in stem cell culture. The use of microwell array technology in stem cell culture is explored in the third section. In the fourth section, we discuss the use of the microfluidic perfusion culture sys‐ tem for stem cell culture, and the last section is a summary of the current state of the art and perspectives of microfluidic technologies in stem cell culture.
How the Network Topology, Traffic Distribution, and Routing Scheme Impact on the Spectrum Usage in Elastic Optical Networks

Elastic Optical Network (EON) has been considered as a promising optical networking technology to architect the next-generation backbone networks. Routing and Spectrum Assignment (RSA) is the fundamental problem in EONs to realize service provisioning. Generally, the RSA is solved by routing the requests with lightpaths first and then assigning spectrum resources to the lightpaths to optimize the spectrum usage. Thus, the spectrum assignment explicitly decide the final spectrum usage of EONs. However, besides the spectrum assignment, there are three other factors, the network topology, traffic distribution and routing scheme, implicitly impact on the spectrum usage. Few related work involves in the implicit impact mechanism. In this paper, we aim to provide a thoroughly theoretical analysis on the impact of the three key factors on the spectrum usage. To this end, two theoretical chains are proposed: (1) The optimal spectrum usage can be measured by the chromatic number of the conflict graph, which is positively correlated to the intersecting probability, \emph{i.e.}, the smaller the intersecting probability, the smaller the optimal spectrum usage; (2) The intersecting probability is decided by the network topology, traffic distribution and routing scheme via a quadratic programming parameterized with a matrix of conflict coefficients. The effectiveness of our theoretical analysis has been validated by extensive numerical results. Meanwhile, our theoretical deductions also permit to give several constant approximation ratios for RSA algorithms.
Isotropic Tensors Under Non-compact Rotation Groups

In the recent past, linearly independent isotropic tensors of rank up to 6, under the compact rotation groups SO(2), SO(3) and SO(4) have been studied in some detail. The present paper extends these studies to the case of linearly independent isotropic tensors under the non-compact rotation groups SO(1, 1), SO(1, 2), SO(1, 3) and SO(2, 2). This is done by using the direct method of explicitly constructing these tensors, proving their linear independence and counting their numbers. Interestingly, it is found that these numbers are identical with the corresponding numbers for the case of the compact groups SO(2), SO(3) and SO(4).
Low energy effective action for Horava-Witten cosmology

As a supersymmetric extension of the Randall-Sundrum model, we consider a 5-dimensional Horava- Witten type theory and derive its low energy effective action. The model we consider is a two-brane system with a bulk scalar field satisfying the Bogomol'nyi-Prasad-Sommerfield (BPS) condition. We solve the bulk equations of motion using a gradient expansion method, and substitute the solution into the original action to get the 4-dimensional effective action. The resultant effective theory can be cast into the form of Einstein gravity coupled with two scalar fields, one arising from the radion, the degree of freedom of the interbrane distance, and the other from the bulk scalar field. We also clarify the relation between our analysis and the moduli approximation.
Classification of Fruits Based on Shape, Color and Texture using Image Processing Techniques

: Food processing industry in any developing nation like India has been always a rough estimate.Food depans on agriculture and horticulture . Agriculture plays an important role in economic development of India. Food processing is need to come up with some new technology so this will make forefront the food sector with best quality . Grading fruits is necessary in evaluating agriculture produce ,meeling quality standards and increasing market value.This paper (envisages ) proposes an system methology for fruits classification based on the shape,color,and texture.This work particulary focused on improving the automation by successfully increasing the detection accuracy of fruits to be processed . This system methology will syccessfuly identifying the different types of fruits by categorizing them into type of category they belong.System involved application of nural network to start with high resolution images of fruits was captured using camera then for faster processing resizing, after the images were resize then shape,colour,texture features were extracted. After the features were extracted the artifical neural network ware used for testing purpose the unclassified images were then fed into ANN system to extract all specified feature and these extracted feature were compared with stored features in neural network on the basis of comparision the fruits are classified.This methodology demonstrates improvement in the classification accuracy using matlab softwear from the previous research work.
INTERACTS WITH THE CHROMATIN REMODELING PROTEIN BRG1

The serotonin-1A (5-HT1A) receptor plays an important role in the regulation of the serotonin (5-HT) system as an autoreceptor on 5-HT neurons. The transcription factor CC2D1A/Freud-1 is a potent repressor of the 5-HT1A promoter in neuronal but not in nonneuronal cells. The clinical relevance of Freud-1 is evident in a naturally occurring mutation, resulting in a truncated form of Freud-1 lacking its C-terminal half, that is associated with non syndromic mental retardation in humans. Thus, it is of interest to clarify the structure and function of Freud-1. As Freud-1 was shown to interact with the transcriptional regulator Brg1 at the 5-HT1A promoter, identification of the structural domains mediating the Brg1/Freud-1 interaction is required to assess the role of Brg1 in Freud-1 repression. In this study, I used pulldown assays with recombinant proteins, co-immunoprecipitation studies and immunofluorescent staining with confocal microscopy to show that Freud-1 interacts directly with the C-terminus of Brg1 and that the C-terminal domain of Freud-1 is required for this interaction.
Dynamic microsets for RAMs

We generalize the concept of Gabow and Tarjan's microsets [3] to dynamic microsets. The dynamic microsets allow the use of direct addressing in a RAM for incremental problems that can be partitioned into subproblems which are merged from time to time. A sequence of operations on dynamic microsets can be performed in O( n + m.a( m, n)) time, where n is the size of the problem and m is the number of queries.
Study of wire-electrical discharge machining parameters of titanium alloy by using taguchi method

Machining of Titanium alloys is difficult due to their chemical and physical properties namely excellent strength, chemical reactivity and low thermal conductivity. Traditional machining of such materials leads to formation of continuous chips and tool bits are subjected to chatter which leads to formation of poor surface on machined surface. In this study, Wire-EDM one of the most popular unconventional machining process which was used to machine such difficult-to-cut materials. Effect of Wire-EDM process parameters namely peak current, pulse-ontime, pulse-off-time, servo voltage on MRR and SR was investigated by Taguchi method. 0.25 mm brass wire was used in this process as electrode material. A surface roughness tester (Surftest 301) was used to measure surface roughness value of the machined work surface. A multi-response optimization technique was then utilized to optimize Wire-EDM process parameters for achieving maximum MRR and minimum SR simultaneously.
CONDENZA: A System for Extracting Abstract from a Given Source Document

Despite the increasingly availability of documents in electronic form and the availability of desktop publishing software, abstracts continue to be produced manually. The purpose of CONDENZA is to develop a system for abstract extraction from a given source document. CONDENZA describes a system on automatic methods of obtaining abstracts. The rationale of abstracts is to facilitate quick and accurate identification of the topic of published papers. The idea is to save a prospective reader time and effort in finding useful information in a given article or report. The system generates a shorter version of a given sentence while attempting to preserve its meaning. This task is carried out using summarization techniques. CONDENZA implements a method that combines apriori algorithm for keyword frequency detection with clustering based approach for grouping similar sentences together. The result from the system shows that our approach helps in summarizing the text documents efficiently by avoiding redundancy among the words in the document and ensures highest relevance to the input text. The guiding factors of our results are the ratio of input to output sentences after summarization.
Students’ Perception and Experiences of A Programme with Cultural and Adventure Initiatives Towards Group Cohesion

The purpose of this exploratory study was to determine the influence of selected cultural and adventure initiatives on the perception and experiences of group cohesion in a multicultural higher education institution. After a 3-day camp, rich qualitative data from students (n = 120) were gathered through focus group discussions and PowerPoint presentations. Using ATLAS.ti, four themes emerged: positive attitude and behaviour, maintaining group level, self-maintaining, and membership attraction and attachment. The findings revealed positive experiences among the participants. It is recommended that follow-up interventions should follow to ensure sustainability.
Free Vibrations of Antisymmetric Angle-Ply Laminated Thin Square Composite Plates

Numerical results are presented for vibration frequencies of antisymmetric angle-ply laminated thin square composite plates having different boundary conditions. Boundary conditions are chosen as 2 adjacent free edges and the remaining edges are simply supported, clamped, or free. The Ritz method, along with the displacement assumed in the form of simple polynomials, is applied to solve the problems. Convergence studies are presented to demonstrate the accuracy of the results. The effects of various parameters such as fibre orientation, number of layers, and boundary conditions upon the natural frequencies are studied.
Geometric Distribution Weight Information Modeled Using Radial Basis Function with Fractional Order for Linear Discriminant Analysis Method

Fisher linear discriminant analysis (FLDA) is a classic linear feature extraction and dimensionality reduction approach for face recognition. It is known that geometric distribution weight information of image data plays an important role in machine learning approaches. However, FLDA does not employ the geometric distribution weight information of facial images in the training stage. Hence, its recognition accuracy will be affected. In order to enhance the classification power of FLDA method, this paper utilizes radial basis function (RBF) with fractional order to model the geometric distribution weight information of the training samples and proposes a novel geometric distribution weight information based Fisher discriminant criterion. Subsequently, a geometric distribution weight information based LDA (GLDA) algorithm is developed and successfully applied to face recognition. Two publicly available face databases, namely, ORL and FERET databases, are selected for evaluation. Compared with some LDA-based algorithms, experimental results exhibit that our GLDA approach gives superior performance.
The Value of Delegation in a Dynamic Agency

In this paper we analyze the value of delegation in a two-period agency. A central management hires an agent to perform a personal effort in each period. Due to time constraints or lack of ability this effort can not be performed by central management. Besides personal effort firm value is influenced by the decision to launch a project which has to be made at the beginning of period two. The project decision can either be delegated to the agent (decentralization) or it can be made by central management (centralization). Under decentralization the agent observes the project’s contribution before its decision. While this captures the benefit of delegation its cost is that the project decision is unobservable and must be motivated together with personal effort via the same incentive contract. In the centralized regime, in contrast, no incentives for the project decision are necessary, however, the project’s actual contribution will not be observed such that the project decision has to be made based on expectations. We analyze optimal performance measurement for both regimes in a linear contracting setting and analyze the variables that affect the value of delegation. We do this for two different contracting regimes: long-term commitment and long-term renegotiation-proof contracts. Trade-offs under both contracting environments differ substantially. In particular, under renegotiation-proof contracts, decentralization might become optimal even if its direct benefit in terms of acquiring specific knowledge about the project vanishes. The reason is that with delegation of the project decision central management implicitly commits to a higher second period incentive rate as personal effort and the project decision must be controlled via the same incentive contract. This is beneficial if renegotiation-proofness requires central management to set too low second-period incentives compared to long-term commitment. A necessary condition for that is, that intertemporal correlation is negative. Contrary to the classical view this result implies that the incentive problem under centralization may become more severe than under decentralization.