Miracle-dz/UniFAR-FTUs huggingface dataset:
Disrupted hippocampal sharp‐wave ripple‐associated spike dynamics in a transgenic mouse model of dementia

High frequency (100–250 Hz) neuronal oscillations in the hippocampus, known as sharp‐wave ripples (SWRs), synchronise the firing behaviour of groups of neurons and play a key role in memory consolidation. Learning and memory are severely compromised in dementias such as Alzheimer's disease; however, the effects of dementia‐related pathology on SWRs are unknown. The frequency and temporal structure of SWRs was disrupted in a transgenic mouse model of tauopathy (one of the major hallmarks of several dementias). Excitatory pyramidal neurons were more likely to fire action potentials in a phase‐locked manner during SWRs in the mouse model of tauopathy; conversely, inhibitory interneurons were less likely to fire phase‐locked spikes during SWRs. These findings indicate there is reduced inhibitory control of hippocampal network events and point to a novel mechanism which may underlie the cognitive impairments in this model of dementia.
Comparison of Classifiers and Statistical Analysis for EEG Signals Used in Brain Computer Interface Motor Task Paradigm

Using the EEG Motor Movement/Imagery database there is proposed an off-line analysis for a brain computer interface (BCI) paradigm. The purpose of the quantitative research is to compare classifiers in order to determinate which of them has highest rates of classification. The power spectral density method is used to evaluated the (de)synchronizations that appear on Mu rhythm. The features extracted from EEG signals are classified using linear discriminant classifier (LDA), quadratic classifier (QDA) and classifier based on Mahalanobis distance (MD). The differences between LDA, QDA and MD are small, but the superiority of QDA was sustained by analysis of variance (ANOVA).
Public Expenditure and Productivity Puzzle: The Case of Northern Cyprus

Since 1974, Northern Cyprus has experienced very low productivity and very slow economic growth, which has further been declining in recent years. In searching for the causes of this poor economic performance emphasis is placed on the lack of investment in infrastructure and education. The present study intends to investigate the hypothesis that “the poor economic performance of Northern Cyprus is due to low levels of investment in infrastructure and education”. In establishing the relationship between output and publicly provided inputs, we specify various Cobb-Douglas production functions by using aggregated and disaggregated time series data on public capital for the period of 1977-1998. Also, recently developed econometric techniques, such as cointegration and the error correction mechanism are used to test the validity of the data. Results indicate that both the long run and short run elasticities of GNP with respect to infrastructure and human capitals are very low and in most cases statistically insignificant. This implies that Northern Cyprus’s poor economic performance in the past is not due to low investments in infrastructure and education, and that further investments in these sectors would not perform a miracle for the economy.
High dimensional similarity search with space filling curves

We present a new approach for approximate nearest neighbor queries for sets of high dimensional points under any L/sub t/-metric, t=1,. ,/spl infin/. The proposed algorithm is efficient and simple to implement. The algorithm uses multiple shifted copies of the data points and stores them in up to (d+1) B-trees where d is the dimensionality of the data, sorted according to their position along a space filling curve. This is done in a way that allows us to guarantee that a neighbor within an O(d/sup 1+1/t/) factor of the exact nearest, can be returned with at most (d+1)log, n page accesses, where p is the branching factor of the B-trees. In practice, for real data sets, our approximate technique finds the exact nearest neighbor between 87% and 99% of the time and a point no farther than the third nearest neighbor between 98% and 100% of the time. Our solution is dynamic, allowing insertion or deletion of points in O(d log/sub p/ n) page accesses and generalizes easily to find approximate k-nearest neighbors.
A Universal Phoneme-Set Based Language Independent Short Utterance Speaker Recognition

In the field of speaker recognition, short utterance speaker recognition (SUSR) has been attracting more and more attention in recent years. Despite the advancement in this technology and use of phonetic cues for speaker recognition, the role of individual phonemes in carrying speaker information is yet quite an open issue. This paper presents a novel idea of using phoneme classes as a basis for SUSR. For the present work, we have restricted ourselves to vowel classes and defined combined vowel classes in two languages, i.e. English and Chinese. These sets are used to develop the universal background phoneme-class model (UBPM) and then for training and testing over conventional GMM-UBM systems. Experimental results have proved that speech segments, as short as phonemes, are surprisingly important areas that carry useful speaker information.
Radical Flank Effects

Radical flank effects (RFEs) are interactive processes involving radical and moderate factions of social movements and third parties outside those movements. They result in detrimental and/or beneficial impacts of radical group actions upon the reputations and effectiveness of more moderate collective actors — typically social movement organizations. The relative “radicalism” or “moderation” of actors is generally defined in terms of the degree of legitimacy that is imputed to their objectives, rhetoric, and tactics by relevant external audiences. Radical flank effects were first studied systematically by Haines (1984, 1988) in his investigations of the American civil rights/black power movements, but other scholars had made reference to RFE-like phenomena in earlier works on the civil rights (Killian 1975), feminist (Freeman 1975), labor (Ramirez 1978) and antinuclear (Barkan 1979) movements. Keywords: movements; radicalism; resource mobilization
Rare Copy Number Variants Identified Suggest the Regulating Pathways in Hypertension-Related Left Ventricular Hypertrophy

Left ventricular hypertrophy (LVH) is an independent risk factor for cardiovascular morbidity and mortality, and a powerful predictor of adverse cardiovascular outcomes in the hypertensive patients. It has complex multifactorial and polygenic basis for its pathogenesis. We hypothesized that rare copy number variants (CNVs) contribute to the LVH pathogenesis in hypertensive patients. Copy number variants (CNV) were identified in 258 hypertensive patients, 95 of whom had LVH, after genotyping with a high resolution SNP array. Following stringent filtering criteria, we identified 208 rare, or private CNVs that were only present in our patients with hypertension related LVH. Preliminary findings from Gene Ontology and pathway analysis of this study confirmed the involvement of the genes known to be functionally involved in cardiac development and phenotypes, in line with previously reported transcriptomic studies. Network enrichment analyses suggested that the gene-set was, directly or indirectly, involved in the transcription factors regulating the “foetal cardiac gene programme” which triggered the hypertrophic cascade, confirming previous reports. These findings suggest that multiple, individually rare copy number variants altering genes may contribute to the pathogenesis of hypertension-related LVH. In summary, we have provided further supporting evidence that rare CNV could potentially impact this common and complex disease susceptibility with lower heritability.
On the reliance of COM Metrics for a C # Project

Can you judge the love of a person? His affection? His intentions? The answer is a big No! However, the bank balance, the assets and even the number of research papers can be measured. Marty Rubin once said “Every line is the perfect length if you don't measure it. ” So, to every software developer his software would be just perfect if there is no metric to measure it. This premise compromises the reliability of software. Therefore it becomes immensely important to be able to measure software as well. In order to accomplish this task, software metrics come to our rescue. The present work analyzes various software metrics, puts them in right perspective and suggests the model to prioritize the metrics so that the software under development can be measured in a comprehensive way with lesser effort. The experiment conducted in order to prove the above premise has also been discussed in the paper. The paper also throws some light on the applicability of software metrics in C# projects. Keywords— Software Metrics, Object Oriented, COM, Reliability.
Detection of line junctions in gray-level images

This paper describes an efficient approach for the detection of line junctions in gray-level images. The algorithm is divided into two steps. First, given the lines extracted from the original image, local line curvature is estimated. For this purpose, two different measures of curvature are proposed: the rate of change of direction of the orientation vector along the line, and the mean of the dot products of orientation vectors within a given neighborhood. The second step involves the localization of junctions. Examples are provided based on experiments with synthetic and real images.
Communications of the Association for Information Systems

Threats to information security are proliferating rapidly, placing demanding requirements on protecting tangible and intangible business and individual assets. Biometrics can improve security by replacing or complementing traditional security technologies. This tutorial discusses the strengths and weaknesses of biometrics and traditional security approaches, current and future applications of biometrics, performance evaluation measures of biometric systems, and privacy issues surrounding the new technology.
Determinants of Mode Choice between Road and Shipping for Freight Transport: Evidence for Four Spanish Exporting Sectors

The estimation of a freight transport demand function using a Conditional Logit model has emphasised the role of cost, transit time, and frequency of shipments as determinants of mode choice. Interviews with exporting firms, freight forwarders, and other transport firms were conducted and data about mode of transport, price, transit time, and other variables was produced. A total of 157 exporting firms located within the Valencian Community were interviewed from October to December 1998. The modes examined were road and sea. Elasticity analysis has found sea transport much more sensitive than road transport to variations in its own costs and changes in transport prices. © 2004 LSE and the University of Bath
Antimicrobial Use and the Influence of Inadequate Empiric Antimicrobial Therapy on the Outcomes of Nosocomial Bloodstream Infections in a Neonatal Intensive Care Unit

Abstract Objective: To evaluate antimicrobial use and the influence of inadequate empiric antimicrobial therapy on the outcomes of nosocomial bloodstream infections (BSIs). Design: Prospective cohort study with nested case-control analysis. Setting: Neonatal intensive care unit (NICU). Methods: All patients weighing 2,000 g or less were enrolled. Data collection included risk factors for nosocomial BSI, admission severity of illness, microbiology, antimicrobial therapy, and outcomes. Inadequate empiric antimicrobial therapy was defined as the use of antibiotics for more than 48 hours after the day that blood cultures were performed that did not cover the microorganisms causing the bacteremia or administration of antibiotics that failed to cover resistant microorganisms. Results: Two hundred twenty-nine patients were enrolled. Forty-five developed nosocomial BSIs. The BSI rates were 11.2, 2.8, and 0 per 1,000 catheter-days for patients weighing 1,000 g or less, between 1,001 and 1,500 g, and between 1,501 and 2,000 g, respectively. After adjustment for severity of illness, the mortality in patients with nosocomial BSI receiving inadequate empiric antimicrobial therapy was higher than in those receiving adequate therapy (adjusted odds ratio [AOR], 5.3; 95% confidence interval [CI95], 1.2-23.2). By multivariate analysis, nosocomial BSI attributed to Candida species (AOR, 6.3; CI95, 1.4-28.0) and invasive procedure prior to onset of BSI (AOR, 6.4; CI95, 1.0-39.0) were associated with administration of inadequate empiric antimicrobial therapy. Conclusions: Administration of inadequate empiric antimicrobial therapy among NICU patients with nosocomial BSI was associated with higher mortality. Additional studies on the role of inadequate empiric antimicrobial therapy and the outcomes of BSIs among NICU patients are needed.
Extracting Wikipedia Historical Attributes Data

In this paper, we describe the collection of a large structured dataset of temporally anchored relational data, obtained from the full revision history of the English Wikipedia. By mining (attribute, value) pairs from this revision history, we are able to collect a comprehensive, temporally-aware knowledge base that contains data on how attributes change over time. We discuss different characteristics of the extracted dataset, which is freely distributed for further study.
Are You Sure You Want to Contact Us? Quantifying the Leakage of PII via Website Contact Forms

Abstract The majority of commercial websites provide users the ability to contact them via dedicated contact pages. In these pages, users are typically requested to provide their names, email addresses, and reason for contacting the website. This effectively makes contact pages a gateway from being anonymous or pseudonymous, i.e., identified via stateful and stateless identifiers, to being eponymous. As such, the environment where users provide their personally identifiable information (PII) has to be trusted and free from intentional and unintentional information leaks. In this paper, we report on the first large-scale study of PII leakage via contact pages of the 100,000 most popular sites of the web. We develop a reliable methodology for identifying and interacting with contact forms as well as techniques that allow us to discover the leakage of PII towards thirdparties, even when that information is obfuscated. Using these methods, we witness the leakage of PII towards third-parties in a wide range of ways, including the leakage through third-party form submissions, third-party scripts that collect PII information from a first-party page, and unintended leakage through a browser’s Referer header. To recover the lost control of users over their PII, we design and develop Formlock, a browser extension that warns the user when contact forms are using PII-leaking practices, and provides the ability to comprehensively lock-down a form so that a user’s details cannot be, neither accidentally, nor intentionally, leaked to third parties
Moving average process underlying the holographic-optical-tweezers experiments

We study statistical properties of the recordings which contain time-dependent positions of a bead trapped in optical tweezers. Analysis of such a time series indicates that the commonly accepted model, i.e., the autoregressive process of first order, is not sufficient to fit the data. We show a presence of the first-order moving average part in the dynamical model of the system. We explain origin of this part as an influence of the high frequency CCD camera on the measurements. The proposed autoregressive moving average model appears to reflect perfectly all statistical features of the high-frequency recording data.
The Legal Implications Arising from Economic and Social Reconstruction as an Aspect of Peace Support Operations

This article asserts that the link between peace and security and stabilization and development, as exemplified by the UN-mandated international presences in Afghanistan, is to be welcomed but that, from the perspective of the laws governing both the use of force and the conduct of warfare, such an evolution is problematic for a number of reasons. One, the broader functions of the military in peace support raises questions for jus ad bellum such as determining whether the basis for the peace enforcement has been achieved, as States and their armed forces engage in stabilization and state-building initiatives as a means to counter breaches of and threats to the peace. Two, the broader functions are problematic for jus in bello as the practical application of such initiatives is not easily incorporated into a body of law that was drafted primarily to deal with inter-state conflict and only provides limited guidance on internal conflict such as that in Afghanistan. Consequently, international law must evolve to clarify the rights and obligations stemming from peace support operations for both States and their military personnel. Author Bio(s) Claire Breen is an Associate Professor at Te Piringa-Faculty of Law at the University of Waikato, New Zealand. Dr Breen's interest in the legal obligations stemming from peace support missions is a reflection of her interest in the confluence between human rights law and the laws of armed conflict and international humanitarian law. This research has been generously supported by the New Zealand Law Foundation in the course of a project entitled "The National and International Legal Obligations and Consequences for New Zealand Arising from its Peace Support Operations". Dr. Breen would like to thank the New Zealand Law Foundation for their generous financial support in the conduct of research for this article. She has previously published extensively in the area of children's rights. Email: cbreen@waikato.ac. nz. This article is available in Peace and Conflict Studies: http://nsuworks.nova. edu/pcs/vol18/iss2/2 Peace and Conflict Studies
Gasification-based Power Generation with CO 2 Production for Enhanced Oil Recovery

Expected economic and CO2 emission performance of two fossil-based technologies for providing new electric generating capacity in the State of California in the time frame 2010-2030 are compared. The two technologies are state of art natural gas combined cycle (NGCC) and coalbased integrated gasification combined cycle (IGCC). In the case of IGCC, it is assumed that nominal 90% of the CO2 emissions are captured, pressurized, and sold for use in conducting enhanced oil recovery (EOR) in the State. This version of IGCC that includes CO2 sequestration is dubbed IGCC+S. The specific carbon emissions to the atmosphere (kg C/net kWh) of IGCC+S are only about 1/5 those of NGCC.
Extreme learning machines for intrusion detection

We consider the problem of intrusion detection in a computer network, and investigate the use of extreme learning machines (ELMs) to classify and detect the intrusions. With increasing connectivity between networks, the risk of information systems to external attacks or intrusions has increased tremendously. Machine learning methods like support vector machines (SVMs) and neural networks have been widely used for intrusion detection. These methods generally suffer from long training times, require parameter tuning, or do not perform well in multi-class classification. We propose a basic ELM method based on random features, and a kernel based ELM method for classification. We compare our methods with commonly used SVM techniques in both binary and multi-class classifications. Simulation results show that the proposed basic ELM approach outperforms SVM in training and testing speed, while the proposed kernel based ELM achieves higher detection accuracy than SVM in multi-class classification case.
Perfect Phylogeny Problems with Missing Values

The perfect phylogeny problem is of central importance to both evolutionary biology and population genetics. Missing values are a common occurrence in both sequence and genotype data, but they make the problem of finding a perfect phylogeny NPhard even for binary characters. We introduce new and efficient perfect phylogeny algorithms for broad classes of binary and multistate data with missing values. Specifically, we address binary missing data consistent with the rich data hypothesis (RDH) introduced by Halperin and Karp and give an efficient algorithm for enumerating phylogenies. This algorithm is useful for computing the probability of data with missing values under the coalescent model. In addition, we use the partition intersection (PI) graph and chordal graph theory to generalize the RDH to multi-state characters with missing values. For a bounded number of states, we provide a fixed parameter tractable algorithm for the perfect phylogeny problem with missing data. Utilizing the PI graph, we are able to show that under multiple biologically motivated models for character data, our generalized RDH holds with high probability, and we evaluate our results with extensive empirical analysis.
Economic Clubs and European Commitment. Evidence from the International Business Cycles

This paper examines the emergence of economic clubs and its coherence with the european commitments. to this end, it analyses business cycle comovements in six industrialised economies, which are pooled into several clusters. results lead to conclude that an english-speaking club (canada, uk, us) is emerging in the last decades, whereas explicit and formal commitments seem to have had a relatively weaker power in determining euro-zone business cycles comovements. while the broad conclusions are consistent with the existing literature the proposed empirical framework is not based on correlations testing, under very few assumptions, the relative cyclical association via the marginal homogeneity in 2x2 contingency tables.
Verifiable Short Signcryption without Random Oracle

Signcryption is a new crypto primitive to model a process achieving privacy and authenticity. Besides privacy and authenticity, non-repudiation is also a pre-requisite property a signcryption for a signcryption scheme. We proposed a publicly verifiable short signcryption scheme which is strong existentially unforgeable under active chosen message attack and is of strong confidentiality under the active chosen cipher-text attack in the flexible unsigncryption oracle. All the security proofs is given standard model without using random oracles.
Excitons in single-walled carbon nanotubes: environmental effect

The properties of excitons in semiconducting single-walled carbon nanotubes (SWCNTs), isolated in vacuum or a medium, and their contributions to the optical spectra of nanotubes are studied within the elementary potential model, in which an exciton is represented as a bound state of two oppositely charged quasi-particles confined to the nanotube surface. The emphasis is given on the influence of dielectric environment surrounding a nanotube on the exciton spectra. For nanotubes in environment with permittivity less than 1.8 the ground-state exciton binding energies exceed the respective energy gaps, while the obtained binding energies of excitons in nanotubes in a medium with permittivity greater than 4 are in good accordance with the corresponding experimental data and consistent with known scaling relation for the environmental effect. The stabilization process of single-electron spectrum in SWCNTs in media with rather low permittivities is discussed.