Miracle-dz/UniFAR-FTUs huggingface dataset:
Glutamate diffusion and AMPA receptor activation in the cerebellar glomerulus

Glutamate release onto a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) is the primary mechanism of fast synaptic transmission in the mammalian brain. Previous studies have revealed that at the cerebellar mossy-fibre to granule cell synapse, the AMPAR mediated synaptic current con sists of a fast-rising and a slow-rising component. The aim of this thesis is to examine the properties of release, diffusion and receptor activation underlying these two components. Two plausible mechanisms could underlie the slow-rising current: spillover of glutamate from neighbouring synaptic contacts and prolonged local release of glutamate via a narrow fusion pore. Using simulations of glutamate diffu sion and receptor activation, I show that lowering the diffusion coefficient of glutamate in the synaptic cleft (Dgjut), which is unknown but can be modulated with macromolecules, has different effects on currents mediated by these two mechanisms. Recordings of the effect of perfusion of dextran (43 kDa) are consis tent with the spillover model and also indicate that Dgiut is approximately 3-fold lower than in free solution. I show using simulations that linear diffusion cannot alone account for the acceleration of the decay of the synaptic current observed at this synapse in lower release probability, but that it can result from non-linear activation of AMPARs. Evidence is presented that diffusion is linear and only one vesicle is released per active zone. In addition, I have extended the diffusion-reaction model of the synapse to develop a framework for examining properties of synaptic AMPARs using glutamate uncaging. I demonstrate that certain kinetic properties of synap tic receptors can be measured using this technique and derive a kinetic model based on preliminary data. Together, these data fill shortcomings in our understanding of synaptic func tion. Based on the present results, I construct a model of synaptic transmission that explains previous observations.
Re-integrating Archaeology: A Contribution to aDNA Studies and the Migration Discourse on the 3rd Millennium BC in Europe

Since aDNA research suggested a marked gene influx from Eastern into Central Europe in the 3rd millennium bc, outdated, simplistic narratives of massive migrations of closed populations have re-appeared in archaeological discussions. A more sophisticated model of migration from the steppes was proposed recently by Kristiansen et al. As a reaction to that proposal, this paper aims to contribute to this ongoing debate by refining the latter model, better integrating archaeological data and anthropological knowledge. It is argued that a polythetic classification of the archaeological material in Central Europe in the 3rd millennium reveals the presence of a new complex of single grave burial rituals which transcends the traditional culture labels. Genetic steppe ancestry is mainly connected to this new kind of burials, rather than to Corded Ware or Bell Beaker materials. Here it is argued that a polythetic view on the archaeological record suggests more complicated histories of migration, population mixtures and interaction than assumed by earlier models, and ways to better integrate detailed studies of archaeological materials with a deeper exploration of anthropological models of mobility and social group composition and the molecular biological data are explored.
On-demand Multi-Rate, Carrier Sense and Hidden Node Interference-Aware Channel Assignment Scheme in Wireless Mesh Network

The proposed interference avoidance channel assignment schemes can provide a significant advantage in term of aggregated throughput by assigning channels only to the active nodes and minimizing the intra-flow and inter-flow interference caused by hidden nodes. However, the negative aspect of the channel assignment schemes for the multi-rate multi-hop wireless mesh networks is the capacity reduction caused by channel reuse over low and high data rate links at the carrier sense and hidden node ranges. This paper proposed an On-demand Multi-Rate, Carrier Sense and Hidden node Interference-Aware channel assignment scheme (AODV-MRCSHDIA) to minimize the interference caused by low rate links at the carrier sense and hidden node ranges on the network throughput. The simulation experiment has been conducted to evaluate the AODVMRCSHDIA over the existing schemes in term of packet delivery ratio and end-to-end delay.
QR Codes and Security Solutions

Identification of objects and places in the real world is important, and 2-D printing code is useful to store identifiers of them. Any camera mobile device with capture function can read content from a barcode tag directly. When a barcode contains important data or privacy information, the risk of security becomes an important problem. Because QR codes simply feature a square barcode with a unique pattern, people have no idea whether the code will take them to reputable information or a site loaded with malware. In this paper, discusses QR codes different data types, attack via QR codes and security solutions. However, since it is easy to modify the content stored in the 2-D code, we must verify whether the identifier written in the 2-D code is indeed issued by the authorized organization.
FOREIGNER DETECTION TRENDY WIRELESS GRIDS BY MULTI PACKET FUNCTION

The primary idea behind our adaptive neighbor discovery schemes should be to provide feedback for that transmitting nodes permitting individuals to prevent transmitting once they've been discovered by their neighbors. During this paper, motivated using the growing prevalence of multipack reception (MPR) technologies for example CDMA and MIMO, we study neighbor discovery in MPR systems which allow packets from multiple synchronized transmitters to obtain received effectively in the receiver. Beginning obtaining a clique of n nodes, we first evaluate an easy Aloha-like formula and show needed time for you to uncover all neighbors wealthy in probability when permitting around k synchronized transmissions. Neighbor discovery is most likely the procedures in configuring and controlling a hidden network. Most existing studies on neighbor discovery assume just one-packet reception model where just only one packet may be received effectively in the receiver. You have to design two adaptive neighbor discovery calculations that dynamically adjust the transmission probability for every node. We consider first a clique of n nodes by which node transmissions are synchronous and the amount of nodes, n, is famous. We show the adaptive calculations yield an apparent difference within the Aloha-like request any clique with n nodes and they are thus order-optimal. Finally, we evaluate our calculations within the general multi-hop network setting. We show the best possible bound of for the Aloha-like formula once the maximum node degree is D that's typically an issue in n worse in comparison with optimal. In addition, when D is large, we show the adaptive calculations are order optimal, i.e., possess a running time, which inserts the lower bound for the problem.
Design of a Wide Tuning-Range, High Swing Fully Differential CMOS VCO With a Differential Tunable Active Inductor

In this paper‎, ‎an inductor-less‎, ‎high frequency tuning range and low power CMOS voltage controlled oscillator (VCO) is presented‎. ‎The VCO can be implemented in 0.18 µm CMOS‎, ‎with 1.8 V supply voltage‎. ‎By using a novel structure‎, ‎a high frequency tuning range‎, ‎low phase noise and low power consumption VCO‎, ‎is obtained‎. ‎In order to increase the frequency tuning range‎, ‎an active inductor is used‎. ‎In addition‎, ‎deep triode region transistors are employed to enhance the swing of the output voltage‎. ‎By using the results of simulation with HSPISE software‎, ‎the tuning range‎, ‎phase noise and power consumption are 5.49-9.6 GHz‎, -‎146 dBc/Hz and 5.99 mW‎, ‎respectively‎.
An user access feature driven semantic cache replacement policy in middleware

The performance of Web applications may be restricted because of large numbers of users interacting with database frequently.Cache in middleware can reduce the cost of the interaction between the requests and the database,and improve the response time.A mechanism of semantic cache is introduced in Web application server.It uses semantic information to match for querying cache,and then traces and analyzes the user access features including user visit timing,visiting content and business association.An efficient cache replacement policy based on the above features is presented.The prototypical experiments shows that the policy is effective at promoting the cache hit rate,and the response time and the throughput of application server can also be improved.
Tracking of Static/Autoconfigured IPv6 addresses

Network operators commonly use Dynamic Host Configuration Protocol (DHCP) to assign IP addresses to the hosts, and track them. However, the tracking capability is lost when stateless autoconfiguration or manual methods are used to assign IPv6 addresses. This document proposes a Dynamic Host Configuration Protocol for IPv6 (DHCPv6) based mechanism that the last hop router can use to convey the hosts' IPv6 addresses for the tracking and logging purposes, without requiring any changes to the hosts.
Learning Management Systems: A Look at the Big Picture

In this chapter, the reader is taken through a “big picture” view of learning management systems, with an emphasis on systems that are used in higher education. Included in this view is a description of common features found in learning management systems and the advantages and limitations of these systems. Also included is the report of a large research study identifying the features used most commonly by students and which of these features are the most and least valued. In addition, the reader is presented with specific resources and options for evaluating, selecting and deploying learning management systems. The chapter concludes with a series of brief profiles of the leading learning management vendors and systems.
Compressing Trees with a Sledgehammer

A variety of problems can be solved more efficiently with the use of compressed trees. The compressed tree method is flexible and can be applied in different ways to solutions for many problems including disjoint set union, nested set union, and path evaluation. The central contribution of this thesis is a unified framework for the analysis of the compressed tree method and a meta-theorem that proves an inverse-Ackermann-type bound for a class of algorithms. The meta-theorem requires only that the compaction method be well-structured and that the other operations maintain a forest structure that admits a wellbehaved rank function. These are the weakest known conditions of any analysis to-date that proves such a bound. We use the framework to give a clean, compact alternative analysis of all but one of the known efficient algorithms for disjoint set union; we provide an explicit proof of optimality for the remaining known optimal method, splicing by rank, which was left as an exercise by Tarjan and van Leeuwen [24]; we prove that a new algorithm for disjoint set union called randomized linking is optimal, giving theoretical backing for some recent experimental results; and finally we proceed to explore the nested set union problem, giving an optimal algorithm for any constant number of partitions as well as a few alternatives for the restricted case of two partitions.
A Language Independent Approach for Recognizing Textual Entailment

Textual Entailment Recognition (RTE) was proposed as a generic task, aimed at building modules capable of capturing the semantic variability of texts and performing natural language inferences. These modules can be then included in any NLP system, improving its performance in fine-grained semantic differentiation. The first part of the article describes our approach aimed at building a generic, language-independent TE system that would eventually be used as a module within a QA system. We evaluated the accuracy of this system by building two instances of it - for English and Romanian and testing them on the data from the RTE3 competition. In the second part we show how we applied the steps described in (1) and adapted this system in order to include it as module in a QA system architecture. Lastly, we show the results obtained, which point out significant growth in precision.
A novel video stabilization method based on FREAK

This paper proposes a novel video stabilization method based on FREAK. That method combines the advantages of the fast speed of binary features and the high efficiency and robustness to parallax of 2D feature trajectories, which avoids inheriting the limitation to parallax from other 2D methods. In order to make the smoothed camera paths as flat as shot by a smoothly moving platform, we take full consideration of 2-degree gradients of the trajectories. This is done by adding a 2-degree regularization to the bundled paths optimization equations. Moreover, a spectral technique is employed to improve the accuracy of original feature matching results. Experiments demonstrate the competitive performance of our proposed method.
Perbandingan Metode Seleksi Fitur pada Spam Filter Menggunakan Klasifikasi Multinomial Naïve Bayes

JULIUS GIGIH DIMASTYO. Comparison of Feature Selection Methods in Spam Filter Using Multinomial Naïve Bayes Classification. Supervised by JULIO ADISANTOSO. Nowadays lots of unwanted email called spam may freely get into the inbox entry. Therefore spam filter software made to classify spam and non-spam email (ham) automatically. Naïve Bayes frequently used today as classification method for it simple and easy to be implemented. Naïve bayes has a good performance to classify multinomial document compared to multivariate Bernoulli when it comes to large vocabulary. Feature selection needed to improve classification model accuracy and make computation process more efficient. There are three feature selection methods used such as inverse document frequency (IDF), mutual information (MI), and chi-square. Based on accuracy level, the result of this study shows that MI is the best feature selection method with 93.77% accuracy and 9507 vocabulary as an identifier.
A single-chip dual-band direct-conversion IEEE 802.11a/b/g WLAN transceiver in 0.18-μm CMOS

This paper presents a single-chip dual-band CMOS direct-conversion transceiver fully compliant with the IEEE 802.11a/b/g standards. Operating in the frequency ranges of 2.412-2.484 GHz and 4.92-5.805 GHz (including the Japanese band), the fractional-N PLL based frequency synthesizer achieves an integrated (10 kHz-10 MHz) phase noise of 0.54°/1.1° for 2/5-GHz band. The transmitter error vector magnitude (EVM) is -36/-33 dB with an output power level higher than -3/-5 dBm and the receiver sensitivity is -75/-74 dBm for 2/5-GHz band for 64QAM at 54 Mb/s.
A Novel Approach For Integrity Auditing And Group User Revocation For Shared Dynamic Cloud Data Access

Users can added various files in the form of text, image, audio, video etc. through the program by using encryption algorithm so that it can be stored on cloud. Thus we can secure data on a cloud. Due to this efficiency is increase and data will be secure on the cloud. Recently, some research considers the problem of secure and efficient public data integrity auditing for shared dynamic data. But this scheme is not secure against collusion of cloud storage server. An efficient public integrity auditing with a secured group user revocation based on vector commitment and group user revocation. A distributed key generation algorithm is used to generate authenticated user passwords across multiple servers and eliminate single point failures. This scheme supports the public checking and efficient user revocation and also provides confidentiality, efficiency and traceability of secure group user revocation. A homomorphic encryption algorithm is also used forcreating unique id for the users. In this system, we purpose a novel public verify technique for the integrity of shared data with efficient user revocation in a mind. By applicability idea of proxy re-signatures. It grant the cloud to re-sign blocks on favor of existing users during the revocation, so that existing users do not need to download and re-sign blocks by themselves. In a public verify , it always able to audit the integrity of shared data without the fetching of whole data from the cloud, even if some part of shared data has been re-sign by cloud. This mechanism is able to support batch auditing by verifying multiple auditing task simultaneously. Experimental results shows that our mechanism can significantly improve the efficiency of user revocation.
Patterns in network security: an analysis of architectural complexity in securing recursive inter-network architecture networks

Recursive Inter-Network Architecture (RINA) networks have a shorter protocol stack than the current architecture (the Internet) and rely instead upon separation of mechanism from policy and recursive deployment to achieve large scale networks. Due to this smaller protocol stack, fewer networking mechanisms, security or otherwise, should be needed to secure RINA networks. This thesis examines the security protocols included in the Internet Protocol Suite that are commonly deployed on existing networks and shows that because of the design principles of the current architecture, these protocols are forced to include many redundant non-security mechanisms and that as a consequence, RINA networks can deliver the same security services with substantially less complexity.
Extracting Medical Knowledge from Crowdsourced Question Answering Website

The medical crowdsourced question answering (Q&A) websites are booming in recent years, and an increasingly large amount of patients and doctors are involved. The valuable information from these medical crowdsourced Q&A websites can benefit patients, doctors and the society. One key to unleash the power of these Q&A websites is to extract medical knowledge from the noisy question-answer pairs and filter out unrelated or even incorrect information. Facing the daunting scale of information generated on medical Q&A websites everyday, it is unrealistic to fulfill this task via supervised method due to the expensive annotation cost. In this paper, we propose a Medical Knowledge Extraction (MKE) system that can automatically provide high-quality knowledge triples extracted from the noisy question-answer pairs, and at the same time, estimate expertise for the doctors who give answers on these Q&A websites. The MKE system is built upon a truth discovery framework, where we jointly estimate trustworthiness of answers and doctor expertise from the data without any supervision. We further tackle three unique challenges in the medical knowledge extraction task, namely representation of noisy input, multiple linked truths, and the long-tail phenomenon in the data. The MKE system is applied to real-world datasets crawled from xywy.com, one of the most popular medical crowdsourced Q&A websites. Both quantitative evaluation and case studies demonstrate that the proposed MKE system can successfully provide useful medical knowledge and accurate doctor expertise. We further demonstrate a real-world application, Ask A Doctor, which can automatically give patients suggestions to their questions.
Visual Forces An Introduction To Design

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Aesthetic measures for screen design

One way to enhance the usability of a computer system is to improve the appearance (beauty) of the user interface. The research reported here concerns making computers easier to learn and use by improving interface aesthetics through the use of aesthetic measures for evaluating screen layouts. We introduce five aesthetic measures: balance, equilibrium, symmetry, sequence, and order and complexity. The results of our informal study of the aesthetic measures demonstrate close relationships between the essence of artists' insights and the measures.
NOVEL APPROACHES FOR THE PRODUCTION OF POLYMER POWDERS FOR SELECTIVE LASER BEAM MELTING OF POLYMERS

The opening of new fields of application of powder-based additive manufacturing methods like selective laser beam melting of polymers currently is hindered by the limited availability of materials showing good processability. So far, virtually only polyamides are available as optimized powder materials. Two innovative methods for production of spherical polymer micro particles for selective laser melting are discussed: The first approach, stirred media milling and rounding, is applicable for a variety of polymers. It will be exemplarily discussed for polyesters and the dependency of product properties (particle size distribution, shape, crystallinity) on the process parameters in the comminution and in the rounding step will be assessed. The second method, melt emulsification, will be demonstrated for polypropylene. Moreover, the possibilities of dry coating to tailor particle properties are illustrated. The influence of powder properties on the processability and on the quality of the obtained devices is outlined.