Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic interactions of excitatory and inhibitory inputs in hypoglossal motoneurones: respiratory phasing and modulation by PKA

The balance of excitation and inhibition converging upon a neurone is a principal determinant of neuronal output. We investigated the role of inhibition in shaping and gating inspiratory drive to hypoglossal (XII) motoneuronal activity. In neonatal rat medullary slices that generate a spontaneous respiratory rhythm, patch‐clamp recordings were made from XII motoneurones, which were divided into three populations according to their inhibitory inputs: non‐inhibited, inspiratory‐inhibited and late‐inspiratory‐inhibited. In late‐inspiratory‐inhibited motoneurones, blockade of GABAA receptors with bicuculline abolished inspiratory‐phased inhibition and increased the duration of inspiratory drive currents. In inspiratory‐inhibited motoneurones, bicuculline abolished phasic inhibition, which frequently revealed excitatory inspiratory drive currents. In non‐inhibited motoneurones, neither bicuculline nor strychnine markedly changed inspiratory drive currents. Inhibitory currents in XII motoneurones were potentiated by protein kinase A (PKA) activity. Intracellular dialysis of the catalytic subunit of PKA or bath application of the PKA activator Sp‐cAMP significantly increased the amplitude of expiratory‐phased IPSCs without any change in IPSP frequency. Inspiratory‐phased inhibition in inspiratory‐inhibited motoneurones was potentiated by Sp‐cAMP. We conclude that inspiratory‐phased inhibition is prevalent in neonatal XII motoneurones and plays an important role in shaping motoneuronal output. These inhibitory inputs are modulated by PKA, which also modulates excitatory inputs.
Efficient SFBC-OFDM technique for broadband cooperative wireless networks over mobile channels

Cooperative diversity is a transmission technique that utilizes distributed relays to improve power and spectral efficiencies by creating virtual a antenna arrays. A major challenge in cooperative systems is the time varying nature and the frequency selectivity of cooperative links. In this paper, we propose a novel technique to enhance the bit error rate (BER) performance of cooperative transmission systems with space-frequency block coded (SFBC) orthogonal frequency division multiplexing (OFDM). We assume the Amplify-and-Forward (AF) protocol jointly with the cooperative transmission protocol in. The proposed scheme eliminates the error floor caused by the difference in frequency response of the channel over two adjacent subcarriers due to the channel frequency-selectivity. Extensive Monte Carlo simulation results show that the system can reduce the BER error floor as compared to the conventional cooperative SFBC-OFDM systems.
Mechanical Alloying Synthesis of Co9S8 Particles as Materials for Supercapacitors

Cobalt sulfide (Co9S8) particles are compounded as the electrode materials of supercapacitors by a mechanical alloying method. They show excellent properties including good cycling stability and high specific capacitance. A supercapacitor is assembled using Co9S8 as the anode and activated carbon (AC) as the cathode. It gains a maximum specific capacitance of 55 F·g−1 at a current density of 0.5 A·g−1, and also an energy density of 15 Wh·kg−1. Those results show that the novel and facile synthetic route may be able to offer a new way to synthesize alloy compounds with excellent supercapacitive properties.
Towards a synthetic analysis of user's information need for more effective personalized filtering services

The consideration of underlying analysis of user's information need is a key requirement in an intelligent filtering environment. However, the majority of current approaches to filtering are relevance-oriented, rather than user-oriented. This is partly because they are issued from fields that have somewhat different perspectives from that of information filtering, but also because of the difficulty of understanding and measuring user's motivations and the way in which the user expects the system to respond. This paper presents an original approach to information analysis and filtering inspired by the novelty detection theory. As well as being able to accurately learn user's information need, the approach has an analytical capacity for better understanding user's need. It provides a new way of looking at user's need in terms of precise, broad, and contradictory profile-contributing criteria. These criteria go on to estimate the relative importance the user might attach to precision and recall. The filtering threshold is then adjusted taking into account this knowledge about user's need. Experimental results on the standard Reuters-21578 collection prove the effectiveness of the approach and confirm the potential usefulness of adapting the filtering results according to the knowledge acquired about user's need.
Hand shape based biometric authentication system using radon transform and collaborative representation based classification

Biometric authentication systems are used to identify individuals based on their unique physiological and behavioral characteristics for access control and security enhancement. In this paper, we propose a novel method of authentication using hand images by collaborative representation based classification (CRC). The contour or hand shape of a query image is extracted by morphological operations and its radon transform is computed along an optimal direction to produce unique one-dimensional feature vector. The feature vector of the query image is then coded over similarly processed training samples from all subjects (or classes) and identified as a member of the class which produces the least reconstruction residual by regularized least square (RLS) instantiation of collaborative representation. Extensive experiments were conducted on a database of 300 images employing two different mathematical operators for dimensionality reduction of acquired feature vector.
The Orai-1 and STIM-1 Complex Controls Human Dendritic Cell Maturation

Ca2+ signaling plays an important role in the function of dendritic cells (DC), the professional antigen presenting cells. Here, we described the role of Calcium released activated (CRAC) channels in the maturation and cytokine secretion of human DC. Recent works identified STIM1 and Orai1 in human T lymphocytes as essential for CRAC channel activation. We investigated Ca2+ signaling in human DC maturation by imaging intracellular calcium signaling and pharmalogical inhibitors. The DC response to inflammatory mediators or PAMPs (Pathogen-associated molecular patterns) is due to a depletion of intracellular Ca2+ stores that results in a store-operated Ca2+ entry (SOCE). This Ca2+ influx was inhibited by 2-APB and exhibited a Ca2+permeability similar to the CRAC (Calcium-Released Activated Calcium), found in T lymphocytes. Depending on the PAMPs used, SOCE profiles and amplitudes appeared different, suggesting the involvement of different CRAC channels. Using siRNAi, we identified the STIM1 and Orai1 protein complex as one of the main pathways for Ca2+ entry for LPS- and TNF-α-induced maturation in DC. Cytokine secretions also seemed to be SOCE-dependent with profile differences depending on the maturating agents since IL-12 and IL10 secretions appeared highly sensitive to 2-APB whereas IFN-γ was less affected. Altogether, these results clearly demonstrate that human DC maturation and cytokine secretions depend on SOCE signaling involving STIM1 and Orai1 proteins.
Investigating the optimal number of attributes to manage knowledge performances

Rules are the most important element in knowledge extraction. The performance or strength of rules will determine how good a model is. Higher accuracy implies that a model is good and vise versa. However, the strength of rules depends on the attributes. The number of attributes in a rule can influence the percentage of accuracy in a model. Most machine learning techniques produce a large number of rules. The consequence is with large number of rules generated, processing time is much longer. This study investigated the performances of rules with different lengths of attribute and identified the optimal number of rule for a good model. The research performed experiments using several data mining techniques. Data of 50 hardware dataset companies which, contains 31 attributes and 400 records was used. Results showed that in terms of number of rules, Genetic Algorithm (GA) produced the highest number of rules followed by Johnson’s Algorithm and Holte’s 1R. The best classifier for extracting rules in this study is VOT (Voting of Object Tracking). In terms of performance of rules, best results comes from rules with 30 attributes, followed by rules with 1 intersection attribute and lastly rules with 3 intersection attributes. Among the three sets of attributes, the set with 3 attributes are considered as the best and three (3) has been identified as the optimal number of attributes.
Invasive candidiasis: turning risk into a practical prevention policy?

Received 16 October 2000; electronically published 20 June 2001. Reprints or correspondence: Dr. Jack D. Sobel, Division of Infectious Diseases, 4 Brush, Harper Hospital, 3990 John R, Detroit, MI 48201 (jsobel@intmed.wayne.edu). Clinical Infectious Diseases 2001; 33:187–9
Advanced optimization method for improving the urban traffic management

The Smart City as a concept of future cities anticipates the smart and efficient traffic management. Current situation of traffic management did not offer a sufficient solution and it is not wise to use the current technology to improve the traffic situation on the city roads. This paper deals with advanced methods for optimization, the genetic algorithms, for using in urban traffic management. Implementation of genetic algorithm and also implementation of classical static solution were provided. We try to prove the advantages of modern optimization methods, which could bring more fluent traffic to the cities and solve the current challenges as i.e. high emissions, big delay, higher probability of accidents. The paper provides comparison measurements of static and dynamic solution in discrete time, discussion of the possible implementation in praxis and evaluation of the advantages and disadvantages for both methods.
An Elias bound on the Bhattacharyya distance of codes for channels with a zero-error capacity

In this paper, we propose an upper bound on the minimum Bhattacharyya distance of codes for channels with a zero-error capacity. The bound is obtained by combining an extension of the Elias bound introduced by Blahut, with an extension of a bound previously introduced by the author, which builds upon ideas of Gallager, Lovász and Marton.
Integration of Antiretroviral Therapy Services into Antenatal Care Increases Treatment Initiation during Pregnancy: A Cohort Study

Objectives Initiation of antiretroviral therapy (ART) during pregnancy is critical to promote maternal health and prevent mother-to-child HIV transmission (PMTCT). The separation of services for antenatal care (ANC) and ART may hinder antenatal ART initiation. We evaluated ART initiation during pregnancy under different service delivery models in Cape Town, South Africa. Methods A retrospective cohort study was conducted using routinely collected clinic data. Three models for ART initiation in pregnancy were evaluated ART ‘integrated’ into ANC, ART located ‘proximal’ to ANC, and ART located some distance away from ANC (‘distal’). Kaplan-Meier methods and Poisson regression were used to examine the association between service delivery model and antenatal ART initiation. Results Among 14 617 women seeking antenatal care in the three services, 30% were HIV-infected and 17% were eligible for ART based on CD4 cell count <200 cells/µL. A higher proportion of women started ART antenatally in the integrated model compared to the proximal or distal models (55% vs 38% vs 45%, respectively, global p = 0.003). After adjusting for age and gestation at first ANC visit, women who at the integrated service were significantly more likely to initiate ART antenatally (rate ratio 1.33; 95% confidence interval: 1.09–1.64) compared to women attending the distal model; there was no difference between the proximal and distal models in antenatal ART initiation however (p = 0.704). Conclusions Integration of ART initiation into ANC is associated with higher levels of ART initiation in pregnancy. This and other forms of service integration may represent a valuable intervention to enhance PMTCT and maternal health.
Duplicate detection of 2D-NMR Spectra

Abstract 2D-Nuclear magnetic resonance (NMR) spectra are used in the (structural) analysis of small molecules. In contrast to 1D-NMR spectra, 2D-NMR spectra correlate the chemical shifts of 1H and 13C at the same time. A spectrum consists of several peaks in a two--dimensional space. The most important information of a peak is the location of its center, which captures the bonding relationships of hydrogen and carbon atoms. A spectrum contains much information about the chemical structure of a product, but in most cases the structure cannot be read off in a simple and straightforward manner. Structure elucidation involves a considerable amount (manual) efforts. Using high-field NMR spectrometers, many 2D-NMR spectra can be recorded in short time. So the common situation is that a lab or company has a repository of 2D-NMR spectra, partially annotated with the structural information. For the remaining spectra the structure in unknown. In case two research labs are collaborating, the repositories will be merged and annotations shared. We reduce that problem to the task of finding duplicates in a given set of 2D-NMR spectra. Therefore, we propose a simple but robust definition of 2D-NMR duplicates, which allows for small measurement errors. We give a quadratic algorithm for the problem, which can be implemented in SQL. Further, we analyze a more abstract class of heuristics, which are based on selecting particular peaks. Such a heuristic works as a filter step on the pairs of possible duplicates and allows false positives. We compare all methods with respect to their run time. Finally we discuss the effectiveness of the duplicate definition on real data.
Technical Efficiency Gains from Port Reform: The Potential for Yardstick Competition in Mexico

The authors show how relatively standard methodologies can help to measure the efficiency gains from reforming the organization of port infrastructure, how those measures can be used to promote competition between ports, and how competition can be built into an incentive-driven regulatory regime. As illustration, they use a case study of port reform in mexico in 1993, the first efficiency analysis of port restructuring in a developing country. Their analysis, which covers 1996-99 and relies on a stochastic production frontier, shows that overall, Mexico has achieved annual efficiency gains of 6-8 percent in the use of port infrastructure since assigning its management to independent, decentralized operators. Changes in relative performance ratings are revealing. They identify consistent sets of leaders and laggards, including some that would not have been identified by partial productivity indicators commonly used in the sector. The authors' main conclusions: 1) Reforms have significantly improved average port performance. 2) The analytically sound performance rankings allowed by the port-specific efficiency measures can help to promote yardstick competition in the sector. These rankings are superior to those that would emerge from use of partial productivity indicators. They account for the joint effects of all inputs on outputs--which is crucial, because it avoids the risk of inconsistent rankings based on different partial indicators, arbitrarily chosen. Developing the database method to measure efficiency in countries with no strong tradition of database development is an enormous task--especially in transport sectors, where the tradition of generating databases useful to policymakers is in its infancy. The most immediate effect of this exercise was to reveal the poverty of the database in the Mexican port sector and the need for regulators to invest in its development.
Comparative Exploration of Document Collections: a Visual Analytics Approach

We present an analysis and visualization method for computing what distinguishes a given document collection from others. We determine topics that discriminate a subset of collections from the remaining ones by applying probabilistic topic modeling and subsequently approximating the two relevant criteria distinctiveness and characteristicness algorithmically through a set of heuristics. Furthermore, we suggest a novel visualization method called DiTop‐View, in which topics are represented by glyphs (topic coins) that are arranged on a 2D plane. Topic coins are designed to encode all information necessary for performing comparative analyses such as the class membership of a topic, its most probable terms and the discriminative relations. We evaluate our topic analysis using statistical measures and a small user experiment and present an expert case study with researchers from political sciences analyzing two real‐world datasets.
Description of a New Galapagos Giant Tortoise Species (Chelonoidis; Testudines: Testudinidae) from Cerro Fatal on Santa Cruz Island

The taxonomy of giant Galapagos tortoises (Chelonoidis spp.) is currently based primarily on morphological characters and island of origin. Over the last decade, compelling genetic evidence has accumulated for multiple independent evolutionary lineages, spurring the need for taxonomic revision. On the island of Santa Cruz there is currently a single named species, C. porteri. Recent genetic and morphological studies have shown that, within this taxon, there are two evolutionarily and spatially distinct lineages on the western and eastern sectors of the island, known as the Reserva and Cerro Fatal populations, respectively. Analyses of DNA from natural populations and museum specimens, including the type specimen for C. porteri, confirm the genetic distinctiveness of these two lineages and support elevation of the Cerro Fatal tortoises to the rank of species. In this paper, we identify DNA characters that define this new species, and infer evolutionary relationships relative to other species of Galapagos tortoises.
On the Usage of LDPC Codes in the McEliece Cryptosystem

In this paper, a new variant of the McEliece cryptosystem, based on Low-Density Parity-Check (LDPC) codes, is studied. Random-based techniques allow to design large fam ilies of LDPC codes with equivalent error correction capability; therefore, in principle, such codes can substitute Goppa co des, originally used by McEliece in his cryptosystem. Furthermore, Quasi-Cyclic (QC) LDPC codes can be adopted in order to reduce the key length, thus overcoming the main drawbacks of the original cryptosystem. Their usage, however, must be subject to cryptanalytic evaluation to ensure sufficient sy stem robustness. The author proves that some widespread familie s of QC-LDPC codes, based on circulant permutation matrices, ar e inapplicable in this context, due to security issues, whils t other families of codes, based on the “difference families” appro ach, are not exposed to the same risk. However, another attack is presented that obliges to adopt very large codes in order to ensure a good level of security against intrusions.
An Extensive Field Survey Combined with a Phylogenetic Analysis Reveals Rapid and Widespread Invasion of Two Alien Whiteflies in China

Background To understand the processes of invasions by alien insects is a pre-requisite for improving management. The whitefly Bemisia tabaci is a cryptic species complex that contains some of the most invasive pests worldwide. However, extensive field data to show the geographic distribution of the members of this species complex as well as the invasion by some of its members are scarce. Methodology/Principal Findings We used field surveys and published data to assess the current diversity and distribution of B. tabaci cryptic species in China and relate the indigenous members to other Asian and Australian members of the complex. The survey covered the 16 provinces where indigenous B. tabaci occur and extends this with published data for the whole of China. We used molecular markers to identify cryptic species. The evolutionary relationships between the different Asian B. tabaci were reconstructed using Bayesian methods. We show that whereas in the past the exotic invader Middle East-Asia Minor 1 was predominant across China, another newer invader Mediterranean is now the dominant species in the Yangtze River Valley and eastern coastal areas, and Middle East-Asia Minor 1 is now predominant only in the south and south eastern coastal areas. Based on mtCO1 we identified four new cryptic species, and in total we have recorded 13 indigenous and two invasive species from China. Diversity was highest in the southern and southeastern provinces and declined to north and west. Only the two invasive species were found in the northern part of the country where they occur primarily in protected cropping. By 2009, indigenous species were mainly found in remote mountainous areas and were mostly absent from extensive agricultural areas. Conclusions/Significance Invasions by some members of the whitefly B. tabaci species complex can be rapid and widespread, and indigenous species closely related to the invaders are replaced.
Multivariate Matching Pursuit in the Analysis of Single-trial Latency of the Auditory M 100 Acquired with MEG

Abstract. A multivariate version of the matching pursuit algorithm (MP) was used in the analysis of auditory evoked fields (AEFs) acquired by means of magnetoencephalography (MEG). Single-trial evoked brain responses were modelled with Gabor functions of certain time of occurrence, temporal width, frequency, and either fixed or varying phase. In particular, trial-to-trial variation of the auditory M100 component was addressed in terms of the phase parameter, with emphasis on the trial dependent amplitude and latency of the M100. The constrained or unconstrained phase turns out to play a significant role in modelling the single-trial M100 wave.
Context inference techniques for a wearable exercise support system

Computer-aided health care services have become more and more popular. This expansion has provided new means to monitor individuals’ health and to provide efficient and accurate feedback. However, it still remains difficult for people to follow fitness and/or weight loss programs because of some lack of discipline or determination. Indeed, most of these programs enforce a workout often too hard for an individual’s physical and psychological capacities. We envision that wearable computers, an integral part of our every day outfits, can assist us in dealing with such problems. In this paper, we propose the ”e-coaching” wearable computing outfit, aiming at providing interactive coaching services for efficient body regulation. Our e-coaching outfit is equipped with multiple sensors and a small PC. The coaching service processes multiple sensor readings about the user’s body and its environment. From this data, it infers a user’s activity status or context and generates coaching messages to guide the user’s training in realtime. We have implemented the ecoaching system and evaluated its context inference accuracy using resource-limited wireless sensor nodes.