Miracle-dz/UniFAR-FTUs huggingface dataset:
Synaptic-type acetylcholine receptors raise intracellular calcium levels in neurons by two mechanisms

Nicotinic acetylcholine receptors (AChRs) located in the postsynaptic membrane on neurons are responsible for mediating fast, excitatory synaptic transmission. If synaptic AChRs are also highly permeable to calcium as reported recently for several kinds of neuronal AChRs, the synaptic receptors could regulate calcium-dependent events in the neurons in concert with normal transmission. Chick ciliary ganglion neurons have two classes of AChRs, one located predominantly in the synaptic membrane and responsible for synaptic signaling through the ganglion and the other located almost exclusively in nonsynaptic membrane and having no known function. The nonsynaptic receptors can readily elevate intracellular calcium concentrations. The experiments reported here indicate that synaptic-type receptors can raise intracellular calcium levels to the same extent as the nonsynaptic receptors and that they do so not only by being permeable to calcium themselves but also by activating voltage-dependent calcium channels (VDCCs). Currents of equivalent amplitude are obtained through the synaptic-type receptors when neurons are bathed in solutions containing either sodium or calcium as the sole extracellular cation. Measuring the effect of ion substitutions on the reversal potential of the receptors and applying the Goldman-Hodgkin-Katz constant field equation indicates the receptors are at least as permeable to calcium as to sodium. When neurons are loaded with the calcium-sensitive dye fluo-3 and challenged with nicotine, both the synaptic-type and nonsynaptic AChRs substantially elevate intracellular calcium levels under physiological conditions, and do so largely by activating VDCCs. Confirmation that synaptic-type AChRs can elevate intracellular calcium levels in the absence of contributions from VDCCs was obtained from voltage-clamp experiments on neurons loaded with fluo-3. The fluorescence signals indicate that the nicotine-induced calcium increases in neurons voltage clamped at rest are nearly as great as those induced in the same neurons when VDCCs are maximally activated by a voltage step. Calcium flux through AChRs may be particularly important for mediating local changes in calcium concentrations near the plasma membrane, which, in turn, could regulate specific membrane- associated calcium-dependent events.
Abnormal Event Detection in Video

Video surveillance has gained importance in security, law enforcement and military applications and so is an important computer vision problem. As more and more surveillance cameras are deployed in a facility or area, the demand for automatic methods for video processing is increasing. The operator constantly watching the video footages could miss a potential abnormal event (e.g. bag being abandoned by a person), as the amount of information/data that has to be handled is high. Most often he has to watch the entire video footage offline, to find the person who abandoned the bag. In this thesis, we present a surveillance system that supports a human operator by automatically detecting abandoned objects and drawing the operator’s attention to such events. It consists of three major parts: foreground segmentation based on Gaussian Mixture Models, a tracker based on blob association and a blob-based object classification system to identify abandoned objects. For foreground segmentation, we assume that video sequences of the background shot under different natural settings are available a priori. The tracker uses a single-camera view and it does not differentiate between people and luggage. The classification is done using the shape of detected objects and temporal tracking results, to successfully categorize objects into bag and non-bag(human). If a potentially abandoned object is detected, the operator is notified and the system provides the appropriate key frames for interpreting the incident.
Can They See It? The Functional Field of View Is Narrower in Individuals with Autism Spectrum Disorder

Although social cognitive deficits have long been thought to underlie the characteristic and pervasive difficulties with social interaction observed in individuals with autism spectrum disorder (ASD), several recent behavioral and neuroimaging studies have indicated that visual perceptual impairments might also play a role. People with ASD show a robust bias towards detailed information at the expense of global information, although the mechanisms that underlie this phenomenon remain elusive. To address this issue, we investigated the functional field of view in a group of high-functioning children with autism (n = 13) and a paired non-ASD group (n = 13). Our results indicate that the ability to correctly detect and identify stimuli sharply decreases with greater eccentricity from the fovea in people with ASD. Accordingly, a probe analysis revealed that the functional field of view in the ASD group was only about 6.62° of retinal eccentricity, compared with 8.57° in typically developing children. Thus, children with ASD appear to have a narrower functional field of view. These results challenge the conventional hypothesis that the deficit in global processing in individuals with ASD is solely due to weak central coherence. Alternatively, our data suggest that a narrower functional field of view may also contribute to this bias.
The Rental Cost of Sunk and Regulated Capital

Standard approaches to estimating the cost of capital are vulnerable to two errors when applied to sunk assets subject to economic regulation. First, investors in sunk assets usually have a valuable ability to delay commitment which is therefore an opportunity cost of investment. Second, economic regulation alters the distribution of returns to capital, and may do so in a way that eliminates profit potential but leaves some risk of losses. This paper studies the impact of, and the interaction between, these effects. A fundamental connection is established between the value of the real option to delay investment, the risk of losses under regulation and the rate of economic depreciation. A practical benefit of this analysis is that existing empirical methods for estimating real options can now be used to estimate the size of the "investment incentive margin" that regulated firms should be allowed.
Survival of the Fittest - Utilization of Natural Selection Mechanisms for Improving PLE

In the current ongoing work we propose the use of tracking and feedback mechanisms in order to improve our Personal Learning Environment (PLE), officially launched in October 2010. The approach can be seen as a necessary prerequisite similar to the darwinistic model of evolution. This means the implemented widgets will be improved (variation) and removed (selection) according to the observations. This paper will describe the backgrounds, methods and some details of the technical implementation.
Write-Aware Replacement Policies for PCM-Based Systems

The gap between processor and memory speeds is one of the greatest challenges that current designers face in order to develop more powerful computer systems. In addition, the scalability of the Dynamic Random Access Memory (DRAM) technology is very limited nowadays, leading one to consider new memory technologies as candidates for the replacement of conventional DRAM. Phase-Change Memory (PCM) is currently postulated as the prime contender due to its higher scalability and lower leakage. However, compared with DRAM, PCM also exhibits some drawbacks, like lower endurance or higher dynamic energy consumption and write latency, that need to be mitigated before it can be used as the main memory technology for the next generation of computers. This work addresses the PCM endurance constraint. For this purpose, we present an analysis of conventional cache replacement policies in terms of the amount of writebacks to main memory that they imply and we also propose some new replacement algorithms for the last-level cache (LLC) with the goal of cutting down the write traffic to memory and consequently, to increase PCM lifetime without degrading system performance. In this paper, we target general purpose processors provided with this kind of non-volatile main memory and we exhaustively evaluate our proposed policies in both single- and multi-core environments. Experimental results show that, on average, compared with a conventional Least Recently Used (LRU) algorithm, some of our proposals manage to reduce the amount of writes to main memory up to 20-30% depending on the scenario evaluated, which leads to memory endurance extensions of up to 20-45%, also reducing the energy consumption in the memory hierarchy by up to 9% and hardly degrading performance.
Sexual health among transgender people in Sweden

ABSTRACT Introduction: Transgender people´s general health and sexual function has previously been studied. However, holistic sexual health—physical, emotional, and relational well-being in relation to sexuality—as both a determinant for and a part of general health is an understudied field in research concerning health among transgender people. There is no research addressing holistic sexual health and sexual health determinants combining quantitative and qualitative data. Aim: To explore and describe holistic sexual health and sexual health determinants among transgender people in Sweden. Methods: For the purpose of this paper, descriptive statistics from a previous web-based survey with 796 respondents and quotes from a previous qualitative interview study with 20 transgender people were combined. Results: Physical, emotional, and relational well-being are all vital aspects for experiencing holistic sexual health; that is, they are all important sexual health determinants, although of different importance to different individuals at different times. Satisfaction with sex life, having an ongoing sexual relationship and having been exposed to disrespectful or discriminatory care are examples of physical, emotional, and relational sexual health determinants that are connected to factors such as condom use, access to respectful STI/HIV-testing and having received reimbursement for sex. Experiences of disrespect and discrimination were reported in both the qualitative and the quantitative data, and in the qualitative data a wish for equity in access to sexual health care is evident. Conclusion: The results provide a broad and extensive insight into transgender people´s sexual health in Sweden. Furthermore it underlines that access to nondiscriminatory health care services is vital, including access to gender-confirming care and different sexual-health-promoting and preventive services such as testing facilities.
Digital Factory – Theory and Practice

Any year automotive exhibitions show new models, merry-go-round of innovations turns faster and faster. Original Equipment Manufacturers (OEMs) introduce any 2 to 3 months new models which very often requires changes of production processes. Extremely short innovation cycles and products customisation significantly change all industries. The innovation is successful only in case, that it is quickly launched on market. The collaboration of single partners is very important not only in product development but in production planning and control too. There exists a lot of chaos and supplementary costs by the launching of new products. These supplementary costs often reach millions of Euros (Jovane.F.;Westkamper,E. & Williams,D., 2009).
Reciprocal abstraction for computer architecture co-simulation

Co-simulation of computer architecture elements at different levels of abstraction and fidelity is becoming an increasing necessity for efficient experimentation and research. We propose reciprocal abstraction for computer architecture cosimulation, which allows the integration of simulation methods that utilize different levels of abstraction and fidelity of simulation. Further, reciprocal abstraction avoids the need to conduct detailed evaluations of individual computer architecture components entirely in a vacuum, which can lead to significant inaccuracies from ignoring the system context. Moreover, it allows an exploration of the impact on the full system resulting from design choices in the detailed component model. We demonstrate the potential inaccuracies of isolated component simulation. Using reciprocal abstraction, we integrate a parallel cycle-level networkon- chip (NoC) component into a detailed but more coarse-grain full system simulator.We show that co-simulation using reciprocal abstraction of the cycle-level network model reduces packet latency error compared to the more abstract network model by 69% on average. Additionally, as simulating a detailed network at the cycle-level can greatly increase simulation time over an abstract model, we implemented detailed network simulator using a GPU coprocessor. The CPU+GPU can reduce simulation time for the reciprocal abstraction co-simulation by 16% for a 256-core target machine and 65% for a 512-core target machine.
Journal of Graph Algorithms and Applications Approximating Clustering Coefficient and Transitivity

Since its introduction in the year 1998 by Watts and Strogatz, the clustering coefficient has become a frequently used tool for analyzing graphs. In 2002 the transitivity was proposed by Newman, Watts and Strogatz as an alternative to the clustering coefficient. As many networks considered in complex systems are huge, the efficient computation of such network parameters is crucial. Several algorithms with polynomial running time can be derived from results known in graph theory. The main contribution of this work is a new fast approximation algorithm for the weighted clustering coefficient which also gives very efficient approximation algorithms for the clustering coefficient and the transitivity. We namely present an algorithm with running time in O(1) for the clustering coefficient, respectively with running time in O(n) for the transitivity. By an experimental study we demonstrate the performance of the proposed algorithms on real-world data as well as on generated graphs. Moreover we give a simple graph generator algorithm that works according to the preferential attachment rule but also generates graphs with adjustable clustering coefficient. The authors gratefully acknowledge financial support from DFG under grant WA 654/13-2 and from the European Commission within FET Open Project COSIN (IST-2001-33555).
Pengaruh Model Pembelajaran Terpadu Dan Kemandirian Belajar Terhadap Kemampuan Menulis Deskripsi

Penelitian ini adalah untuk mendapatkan informasi mengenai efek dari model pembelajaran terpadu dan belajar mandiri untuk kemampuan menulis deskriptif. Penelitian ini dilakukan dengan menggunakan model eksperimen dengan desain analisis faktorial 2x2 di pengujian hipotesis. Dalam penelitian ini, 22 dari cluster random sampling 80 siswa. Penelitian ini difokuskan pada tiga aspek; model pembelajaran terpadu dan belajar mandiri untuk kemampuan menulis deskriptif. Data dikumpulkan dengan tes menulis deskriptif dan dianalisis dengan analisis jalur. Hasil analisis dapat disimpulkan bahwa (1) menulis deskriptif siswa keterampilan diberi model pembelajaran tematik terpadu lebih tinggi dari siswa yang diberi terfragmentasi, (2) menulis deskriptif siswa keterampilan dalam kelompok siswa yang telah independen pembelajaran tinggi diberikan model pembelajaran terpadu tematik terpadu lebih besar daripada sekelompok siswa diberi pembelajaran terfragmentasi, (3) siswa kemampuan menulis deskriptif dalam kelompok siswa yang memiliki belajar mandiri rendah mengingat tentang belajar terfragmentasi lebih tinggi dari kelompok siswa diberi tentang model pembelajaran tematik terpadu, (4) ada interaksi antara pembelajaran dan belajar mandiri dengan keterampilan menulis deskriptif
Automatic recognition of epileptic seizure in EEG via support vector machine and dimension fractal

Support vector machine (SVM) is a machine learning technique widely applied in classification problems. SVM are based on the Vapnik's Statistical Learning Theory, and successively extended by a number of researchers. On the order hand, the electroencephalogram (EEG) signal captures the electrical activity of the brain and is an important source of information for studying neurological disorders. In order to extract relevant information of EEG signal, a variety of computerized-analysis methods have been developed. Recent studies indicate that methods based on the nonlinear dynamics theory can extract valuable information from neuronal dynamics. However, many these of methods need large amount of data and are computationally expensive. From chaos theory, a global value that is relatively simple to compute is the fractal dimension (FD), it can be used to measure the geometrical complexity of a time series. The FD of a waveform represents a powerful tool for transient detection. In analysis of EEG this feature can been used to identify and distinguish specific states of physiologic function. A variety of algorithms are available for the computation of FD. In this work, we employ SVM to classify the EEG signals from healthy subjects and epileptic subjects using as the features vector the FD. From the experimental results, we can see that classification based on SVM with FD perform well in EEG signals classification, which indicates this classification method is valid and has promising application.
Outlier detection using naïve bayes in wireless ad hoc networks

Nowadays, security is one of the most significant concerns when constructing a flexible and improvisational network. For a wireless ad hoc network, which is exposed to an open and cooperative environment, its vulnerability needs a more effective protection for the validation of information sharing, when compared to traditional networks. At present, trust gains extensive attention as it is regarded as a well-known distributed management method to perceive abnormal behavior of other nodes. In this paper, we emphasize the importance of node cooperation, especially for the sharing of trust information. Thereby, an outlier detection scheme is presented based on Naïve Bayes algorithm, which is used to predict the reliability of trust information provided by other adjacent nodes. We examine the scheme based on our design criteria and attack models. Through the security analysis, Naïve Bayes makes the trust-based outlier detection more suitable and reliable for distributed networks.
A Fluorescent Glycolipid-Binding Peptide Probe Traces Cholesterol Dependent Microdomain-Derived Trafficking Pathways

Background The uptake and intracellular trafficking of sphingolipids, which self-associate into plasma membrane microdomains, is associated with many pathological conditions, including viral and toxin infection, lipid storage disease, and neurodegenerative disease. However, the means available to label the trafficking pathways of sphingolipids in live cells are extremely limited. In order to address this problem, we have developed an exogenous, non-toxic probe consisting of a 25-amino acid sphingolipid binding domain, the SBD, derived from the amyloid peptide Aβ, and conjugated by a neutral linker with an organic fluorophore. The current work presents the characterization of the sphingolipid binding and live cell trafficking of this novel probe, the SBD peptide. SBD was the name given to a motif originally recognized by Fantini et al [1] in a number of glycolipid-associated proteins, and was proposed to interact with sphingolipids in membrane microdomains. Methodology/Principal Findings In accordance with Fantini's model, optimal SBD binding to membranes depends on the presence of sphingolipids and cholesterol. In synthetic membrane binding assays, SBD interacts preferentially with raft-like lipid mixtures containing sphingomyelin, cholesterol, and complex gangliosides in a pH-dependent manner, but is less glycolipid-specific than Cholera toxin B (CtxB). Using quantitative time-course colocalization in live cells, we show that the uptake and intracellular trafficking route of SBD is unlike that of either the non-raft marker Transferrin or the raft markers CtxB and Flotillin2-GFP. However, SBD traverses an endolysosomal route that partially intersects with raft-associated pathways, with a major portion being diverted at a late time point to rab11-positive recycling endosomes. Trafficking of SBD to acidified compartments is strongly disrupted by cholesterol perturbations, consistent with the regulation of sphingolipid trafficking by cholesterol. Conclusions/Significance The current work presents the characterization and trafficking behavior of a novel sphingolipid-binding fluorescent probe, the SBD peptide. We show that SBD binding to membranes is dependent on the presence of cholesterol, sphingomyelin, and complex glycolipids. In addition, SBD targeting through the endolysosomal pathway in neurons is highly sensitive to cholesterol perturbations, making it a potentially useful tool for the analysis of sphingolipid trafficking in disease models that involve changes in cholesterol metabolism and storage.
A SEMANTIC WIKI FOR COLLABORATIVE KNOWLEDGE FORMATION

In this paper, we explore some of the apparent problems in adopting semantic technologies for content management and investigate a methodology and a tool to overcome these barriers. Our approach tries to benefit from both the networked collective intelligence of social software and the obvious need for methodologies and well-defined explicit semantics in our information and knowledge systems in order to support business processes.
Learning Impact Evaluation of the serious game "Cultural Awareness - Afghanistan Pre-deployment"

Attention to human factor in conducting any type of military/security operations is currently an objective of utmost importance in the context of troop training within NATO. To this purpose, a number of serious games were developed, addressing different aspects of cultural awareness and correctness in approaching human beings during a mission. A significant example is “Afghanistan Pre-deployment – Cultural Awareness”, a serious game widely adopted in NATO Defense Schools to support pre-deployment training of troops for the International Security Assistance Force (ISAF) missions in Afghanistan. In the context of GALA, the European Network of Excellence on Serious Games, the Romanian National Defense University (MAN) and NATO-STO CMRE conducted a user study particularly focused on the learning impact of this serious game. The study was first run in parallel on different typologies of players (soldier trainees at MAN; and civilian/military staff at CMRE) in order to get different perspectives in the game test and evaluation; results of respective analyses were compared, in order to evaluate the effectiveness of this type of serious game as a learning tool. A preliminary correlation study was conducted between users’ perception of the game and their respective background and level of engagement.