Miracle-dz/UniFAR-FTUs huggingface dataset:
Thalamocortical synapses of pyramidal cells which project from SmI to MsI cortex in the mouse

Electrolytic lesions were made of the nucleus ventralis posterior pars lateralis thalami and of the nucleus posterior thalami in male CD/1 mice to label thalamocortical axon terminals in mouse SmI cortex. Pyramidal cells in layers II through V of SmI cortex were labeled by the retrograde transport of horseradis peroxidase injected into ipsilateral MsI. Numerous pyramidal cells, particularly in the more superficial layers of SmI cortex, were filled with reaction product so that even their dendritic spines and local axon collaterals were clearly visible. Six well‐filled pyramidal cells with somata in layers III and IV were serial thin‐sectioned, and portions of their dendrites in layer IV were examined with the electron microscope to determine the distribution of their thalamocortical and other synapses. It was found that, in general, different dendrites of a single pyramidal cell formed similar proportions of thalamocortical synapses and that the six pyramidal cells, as a group, also formed similar proportions of thalamocortical synapses with their dendrites in layer IV. In contrast, when the thalamocortical connectivity of the six cells was considered as a function of their depths within the cortex, a clear trend was seen for the proportion of thalamocortical synapses to increase with increasing proximity of the cell body to layer IV. A hypothesis based on the timing of developmental events is proposed to account for this observation.
Fibrin D-dimer, Markers of Coagulation Activation and the Risk of Major Ischaemic Heart Disease in the Caerphilly Study

Summary We have previously reported that plasma fibrin D-dimer (a marker of turnover of cross-linked fibrin) showed a strong and independent association with incident ischaemic heart disease (IHD) in the Caerphilly Study cohort of 1,998 men aged 49-65. To establish the specificity of this finding, we assayed plasma samples from this cohort with a more specific assay for fibrin D-dimer: this showed an association with incident IHD which was at least as strong and independent as that for the original assay (odds ratio, OR for top fifth compared to bottom fifth 3.79; 95% CI 1.77-8.10; p < 0.0001). To establish potential causes of the increased fibrin turnover, we also assayed several potential markers of coagulation activation or thrombotic tendency (prothrombin fragment F1+2, thrombin-antithrombin complexes, factor VIIc, activated partial thromboplastin time [APTT] and activated protein C resistance): none of these variables were associated with incident IHD in this cohort. We suggest that further studies are required to establish the causes of increased cross-linked fibrin turnover, which is associated with incident IHD in the general population when measured by a specific assay.
Therapy for naming disorders: Revisiting, revising, and reviewing

Background: Impairments of word retrieval and production are a common and distressing feature of aphasia, and much clinical time is devoted to attempts at their remediation. There are now many research papers devoted to case studies examining treatments for word-retrieval impairments using a wide range of tasks with individuals who have varying levels of impairment. Aims: This paper aims to continue the selective review of this literature carried out by Nickels and Best (1996a). It summarises in table form those published papers since 1980 which present single case studies of treatment for word-retrieval impairments and which satisfy minimal methodological criteria. Main Contribution: Several main themes are derived from the literature and discussed in more detail, these include strategic approaches and facilitative or repair approaches to remediation, the contrast between semantic and phonological tasks in therapy, generalisation in therapy tasks and the relationship between impairment, therapy task, and outcome. Further discussion relates to the relationship between impairment level treatments, and measures of disability and handicap, and between therapy research and therapy practice. Conclusions: There are now many research papers devoted to impairments of word retrieval, and there can be no doubt that therapy for word-retrieval impairments can be highly successful, resulting in long-term improvements which can be of great communicative significance for the individual with aphasia. However, predicting the precise result of a specific treatment task with a specific individual with certainty is still not possible. For clinicians the recommendation is to use analyses of functional impairments to guide the choice of task, but to ensure that efficacy is tested and not assumed. Furthermore, structured multi-modal and multicomponent tasks (e.g., “semantic” or “phonological” cueing hierarchies) may hold the most promise for many individuals. For researchers, there remains a need to further dissect tasks, impairments, and their interactions across series of single cases.
Mood disorders in intellectual disability

Purpose of review This article examines reviews and research on the diagnosis and treatment of mood disorders in people with intellectual disability published from September 2004 to December 2005. Recent findings Patients with intellectual disability have limitations in verbal ability, and with increasing levels of disability may have an atypical clinical presentation. Thus, methods to diagnose mood disorders were a major research focus. Informant-rating scales and two self-report instruments provided data on thought patterns, aberrant behavior, appetite, and suicidality. Behavioral symptoms such as aggression were frequently associated with mood disorders. Pharmacotherapy and electroconvulsive therapy were found to be effective treatments. Mood disorders were frequently identified in people with intellectual disability, although suicide was still quite rare. Summary Patients with milder levels of disability can use self-report measures and can be diagnosed using standard criteria with little modification. For those with more severe disability, diagnosis is challenging and often requires the use of residual categories. Atypical clinical presentation, including maladaptive behaviors, lent support for ‘behavioral equivalent’ substitutes of standard criteria. Typical pharmacological agents were effective for depression and electroconvulsive therapy for treatment-resistant bipolar disorder.
Interest Rate Volatility and Nominalization

Most Latin American economies in the 1980’s and early 1990’s were burdened with extremely high inflation rates. Chile’s strategy to strengthen its financial market was to rely on inflation-linked securities. Indeed, indexation pervaded the whole economy for almost thirty years. However, the sharp decrease in the annual inflation rate over the last decade— from 26 percent in 1990 to 4 percent in 2001—led the Central Bank of Chile to set its monetary policy interest rate in nominal terms from August 2001 onwards. This paper analyzes the effect of nominalization on the behavior of nominal and inflation-linked interest rates. We find that nominalization has made nominal interest rates less volatile, while the opposite holds for inflation-linked interest rates. We use different volatility measures, and test the presence of structural breaks in unconditional variance by the Iterative Cumulative Sums of Squares (ICSS) algorithm. In addition, we model the co-movements of short and long maturity interest rates in the presence of volatility breakpoints. We also show that deposits in Chilean pesos have now a higher share of total deposits, and that trading of derivatives to hedge inflation risk has become much more active since nominalization took place. At the same time, the market of derivatives on interest rates also seems to have taken off.
Non-rigid object tracking by adaptive data-driven kernel

We derive an adaptive data-driven kernel in this paper to simultaneously address the kernel scale/orientation selection problem as well as the constant kernel shape in deformable object tracking applications. Level set technique is novelly introduced into the mean shift sample space to implement kernel evolution and update. Since the active contour model is designed to drive the kernel constantly to the direction that maximizes target likelihood, the kernel can adapt to target shape variation simultaneously with the mean shift iterations. Thus, it can give a better estimation bias to produce accurate shift of the mean and successfully avoid performance loss stemmed from pollution of the non-object regions hiding inside the kernel. Experimental results on a number of challenging sequences validate the effectiveness of the technique.
On use of big data for enhancing network coverage analysis

Proliferation of data services has made it mandatory for operators to be able identify geographical regions with 3G connectivity discontinuity in a scalable and cost-efficient manner. The currently used methods for such analysis are either costly - such as in drive tests, partly unreliable - such as in network simulation approaches, or are not precise enough - such as in base station key performance indicators (KPI) based approaches. In this paper, towards addressing these inadequacies, we propose a 3G coverage analysis method that makes use of “big data” processing schemes and the vast amounts of network data logged in mobile operators. In the proposed scheme, the BSSAP mobility and radio resource management messages between the BSS and MSC nodes of the operator network are processed to identify inter-technology handovers from 3G (WCDMA) access to 2G (EDGE, GPRS, GSM). Demonstrative examples show that the proposed mechanism produces accurate and precise results, outperforming the base station KPI-based approach.
A Scalable Multi-Tenant Architecture for Business Process Executions

Cloud computing, as a concept, promises cost savings to end-users by letting them outsource their non-critical business functions to a third-party in pay-as-you-go style. However, to enable economic pay-as-you-go services, the end-users need Cloud middleware that maximizes sharing and support near-zero cost for unused applications. Multi-tenancy, which let multiple tenants to share a single application instance securely, is a key enabler for building such a middleware. On the other hand, Business processes capture Business logic of organizations in an abstract and reusable manner, and hence play a key role in most organizations. This paper presents the design and architecture of a scalable Multi-tenant Workflow engine while discussing in detail the potential use cases of such architecture. Primary contributions of this paper are motivating workflow multi-tenancy, and the design and implementation of a scalable multi-tenant workflow engine that enables multiple tenants to run their workflows securely within the same workflow engine instance without modifications to the workflows. Furthermore, the workflow engine supports process sharing and process variability across the tenants and discusses its ramifications.
Experiments and identification of an ostraciiform fish robot

The ostraciiform swimming mode allows the simplest mechanical design and control for fish robot swimming. Propulsion is achieved via the flapping of caudal fin without the undulatory body motion. In this research, some rigid caudal fins were used to identify the effects of flapping frequency and flapping amplitude on the swimming velocity of an ostraciiform fish robot. Experiments were conducted to measure the drag coefficient and the added mass of the fish robot. The experimental data were identified with a theoretical model of caudal fin propulsion. It can be shown that the terminal velocity was proportional to the flapping frequency and to the 2/3 power of the flapping amplitude.
An Ensemble method for Content Selection for Data-to-text Systems

We present a novel approach for automatic report generation from time-series data, in the context of student feedback generation. Our proposed methodology treats content selection as a multi-label classification (MLC) problem, which takes as input time-series data (students' learning data) and outputs a summary of these data (feedback). Unlike previous work, this method considers all data simultaneously using ensembles of classifiers, and therefore, it achieves higher accuracy and F- score compared to meaningful baselines.
The influence of social interaction on meaning construction in a virtual community

As proposed by social constructive theorists, meaningful learning and individual development were achieved through social interaction. To foster social interaction among students, this study formed an online learning community in which they played multiple roles as writers, editors and commentators. In playing different roles, they read peers' texts, edited peers' errors, evaluated peer editors' corrections and finally reconstructed their own texts. Results of this study showed that the multiple roles they played allowed them to have opportunities to view their own texts from others' perspectives. Based on these perspectives, they were more willing to acquire information from and contribute information to peers. All of this extensive information acquisition and contribution resulted in meaning construction of texts as active students improved their final drafts in both local revision (grammatical correction) and global revision (the style, organisation and development of a text) after receiving and evaluating feedback from peer editors. Their final drafts were very different from those of passive students whose first and final drafts were almost the same despite some grammatical revisions. This study suggests that, rather than relying only on an examination of students' final drafts, there may be benefits in teachers encouraging students to actively participate in social interaction by reading peers' texts, editing peers' errors and evaluating peer editors' corrections during text revisions. [ABSTRACT FROM AUTHOR]
A new quadratic boost converter with PFC applications

A novel quadratic boost converter capable of delivering a high output voltage is introduced. Dc-dc operation in continuous conduction mode (CCM) and discontinuous inductor current mode (DICM) are analyzed. A simple and versatile feedforward (FF) circuit is proposed in order to be used with the new converter when operated in CCM. Another application is the use of the converter as a power factor correction (PFC) circuit. At low power levels DICM operation is chosen, because of the converter natural capability of emulating a resistor at low frequency. The PFC solution at high power levels is based on CCM operation of the converter, in conjunction with the proposed feedforward circuit. Design equations, simulation results and merit parameters are presented for all the investigated topologies.
Android malware detection using multivariate time-series technique

Recently, use of smart devices has continued to spread in parallel with their performance improvement. The proliferation of smart devices has led to an emergence of various services such as messengers, SNS and smart banking, and brought convenience in using the services. However, the threat called security vulnerabilities is being faced on the other side. The damages suffered from such a threat are personal information leakage, unreasonable charging, root permission acquisition and so on. In addition, it is said that Android, which is considered as the most vulnerable operating system among the smart devices' operating systems, has the greatest damage of malware codes. Accordingly, this paper proposes a technique to detect malicious codes based on Android devices by using the multivariate time-series analysis. A variety of resource information is integrated into a resource to organize data, and an autoregressive moving average model of the time-series models is used to carry out the modeling. The modeled data is matched with real data to detect malicious codes. The proposed method's validity and excellence is suggested through this experimental result.
An Introduction to Modern Pricing of Interest Rate Derivatives

This thesis studies interest rates (even negative), interest rate derivatives and term structure of interest rates. We review the different types of interest rates and go through the evaluation of a derivative using risk-neutral and forward-neutral methods. Moreover, the construction of interest rate models (term-structure models), pricing of bonds and interest rate derivatives, using both equilibrium and no-arbitrage approaches are discussed, compared and contrasted. Further, we look at the HJM framework and the LMM model to evaluate and simulate forward curves and find the forward rates as the discount factors. Finally, the new framework (after financial crisis in 2008), under the collateral agreement (CSA) has been taken into consideration.
On the performance of cubic networks under correlated traffic pattern

The efficiency of a multicomputer is critically dependent on the performance of its interconnection network. This paper presents a new analytical model for circuit-switched cubic networks in the presence of correlated traffic pattern, which is a typical scenario for multimedia applications. A message in circuit switching may need a number of connection attempts before successfully setting up a path from source to destination. The proposed model uses the approach of superposing infinite correlated traffic streams to capture the effective traffic entering the network from a source, which includes the traffic generated by the source node and the traffic due to many connection attempts. Simulation experiments reveal that the model exhibits a good degree of accuracy under various operating conditions.
Model Selection to Characterize Performance Using Genetic Algorithms

The TIA modeling framework provides analytical models of the performance of parallel applications. The resulting models are obtained using model selection techniques and are accurate enough for various purposes. Its main drawback is that the completion time depends on the number of candidate models and, in some situations, it becomes critical. In this work, a genetic algorithm is proposed for reducing the time for searching of the best candidate model. The use of this genetic algorithm to obtain the performance model of the linear implementation of the broadcast collective communication in a cluster of multicores is shown.
On the Continuous Limit of GARCH

GARCH processes constitute the major area of time series variance analysis hence the limit of these processes is of considerable interest for continuous time volatility modelling. The limit of the GARCH(1,1) model is fundamental for limits of other GARCH processes yet it has been the subject of much debate. The seminal work of Nelson (1990) derived this limit as a stochastic volatility process that is uncorrelated with the price process but a subsequent paper of Corradi (2000) derived the limit as a deterministic volatility process and several other contradictory papers followed. In this paper we reconsider this continuous limit, arguing that because the strong GARCH model is not aggregating in time it is incorrect to examine its limit. Instead it is legitimate to use the weak definition of GARCH that is time aggregating. We prove that its continuous limit is a stochastic volatility model that reduces to Nelson’s GARCH diffusion only under certain assumptions. In general, the weak GARCH limit has correlated Brownian motions in which both the variance diffusion coefficient and the price-volatility correlation are related to the skewness and kurtosis of the physical returns density.
A Special Purpose Signature Scheme for Secure Computation of Traffic in a Distributed Network

We study the problem of traffic aggregation in a network with some natural security constraints. Here each node i has traffic (number of packets) mi and they forward this information through the network to a server node which wishes compute ∑mi. The sever node should not be able to know any additional information about mi’s and an intermediate node should not be able to tamper (without detection) the traffic information it is forwarding. We formalize this problem and suggest a solution using a variant of aggregate signatures, and prove its security using standard hardness assumptions.
Economies of Convergence: Towards a Redefinition of the Energy Business?

Traditionally the energy business is known as a very distinct economic and technical activity that is performed by specialized firms. Even within the energy sector, there was often a clear differentiation between electricity and gas firms. As one of the surprising consequences of the ongoing process of liberalization these once sharp differences seem to become less rigid. Regulatory models of liberalization applied to the energy industry apparently fit to different sectors like telecom, water or railroad transportation. Energy firms develop into new businesses, including other utilities like water or telecom; but even insurance, financial services, the exploitation of professional soccer clubs, selling shoes, or providing emergency assistance for automobiles are in some cases considered as complementary to the provision of electricity or gas. There are also innovative new comers to the energy market that in the past had little or no affiliation with this specific business, like for instance grocery stores, environmental or religious organizations, or patrol stations. Even with respect to the ‘hard’ technology alternative applications are considered, as for example using gas pipelines to roll-out fiber optic cables or electricity lines for data communication. Not all of these developments are completely new, but they certainly gained considerably interest and attracted significant investment in line with the ongoing liberalization process. This movement or tendency is referred to as convergence. This article analyzes how convergence contributes to a redefinition of the boundaries of the energy business. Based on a typology of different cases of convergence (paragraph 2) some fundamental economic drivers are identified that support this movement (paragraph 3). Taking these economies as a reference, it is possible to elaborate on the perspectives of convergence with respect to the technical and economic boundaries of the energy business (paragraph 4). Finally opportunities and challenges of convergence with respect to business and regulation are discussed.
A threshold explains modulation of neural responses to opposite-contrast stereograms

Disparity-sensitive neurons respond to contrast-inverted stereograms (aRDS) that do not evoke depth percepts. This is in conflict with the idea that such neurons are the direct correlate of depth perception. However, the output of neurons responding to aRDS may be further processed: neurons at later processing stages show weaker responses to aRDS than early stage neurons. Here, we show that such a response hierarchy emerges in a three-layered neural network. A numerical analysis demonstrates that threshold operations can largely explain the network's behavior as well as the electrophysiological data. An extension of the energy neuron model for disparity-sensitive neurons predicts increased responses to aRDS for an identifiable sub-class of cells and can thus be tested in electrophysiological experiments.