Miracle-dz/UniFAR-FTUs huggingface dataset:
Opiates suppress a resting sodium-dependent inward current and activate an outward potassium current in locus coeruleus neurons

The opioid peptide met-enkephalin (met-ENK) produces an outward current with an increase in input conductance in locus coeruleus (LC) neurons. This current has been attributed to an opening of potassium channels. However, the opioid-induced current tends to reverse at potentials more negative than the expected potassium reversal potential (EK) or does not reverse at all. Since lack of reversal can occur if there is a simultaneous increase in one conductance and a decrease in a second conductance, we tested the possible contribution of a second conductance to the opioid-induced outward current in LC neurons. Biochemically, opiates inhibit adenylate cyclase in LC neurons and cAMP- active agents produce a sodium-dependent inward current in these neurons. This current is also present at rest, as sodium substitution hyperpolarizes LC neurons. By inhibiting adenylate cyclase, could opiates be turning off this current? To evaluate this possibility, we used intracellular voltage-clamp technique in rat LC slices, and studied the effect of sodium substitution on the opiate response. Replacement of external sodium (80%) with Tris or choline caused (1) an outward current with a decrease in input conductance and (2) an approximately 50% decrease in the met-ENK-induced outward current with a shift in its reversal potential toward EK. Extracellular Ba2+, a K+ channel blocker, also partially reduced the opiate response, but it shifted its reversal potential away from EK. The met-ENK-induced outward current was almost totally abolished by combined sodium substitution and extracellular Ba2+ in an additive manner. (ABSTRACT TRUNCATED AT 250 WORDS)
Fuzzy sliding mode control for trajectory tracking and force compensation of a robotic haptic interface

This paper presents an integration of successfully tried out robust control techniques applied to trajectory tracking of a mechanical manipulator which operates as a robotic rehabilitation system for upper limb diseases. This controller combines the robustness of the sliding mode approach with the efficiency and adaptability of the fuzzy logic. Furthermore, this control law includes force compensation to yield haptic interaction with the patient during the rehabilitation tasks. The satisfying simulation results not only encourage implementing this controller on high performance hardware, but they were also useful to validate the selected actuators and led the design and development of the power electronics for the robotic workstation.
Depression and Incident Dementia. An 8-Year Population-Based Prospective Study

Aims The aim of the study was to investigate the impact of depression (categorical diagnosis; major depression, MD) and depressive symptoms (dimensional diagnosis and symptom patterns) on incident dementia in the German general population. Methods Within the Leipzig Longitudinal Study of the Aged (LEILA 75+), a representative sample of 1,265 individuals aged 75 years and older were interviewed every 1.5 years over 8 years (mean observation time 4.3 years; mean number of visits 4.2). Cox proportional hazards and binary logistic regressions were used to estimate the effect of baseline depression and depressive symptoms on incident dementia. Results The incidence of dementia was 48 per 1,000 person-years (95% confidence interval (CI) 45–51). Depressive symptoms (Hazard ratio HR 1.03, 95% CI 1.01–1.05), and in particular mood-related symptoms (HR 1.08, 95% CI 1.03–1.14), showed a significant impact on the incidence of dementia only in univariate analysis, but not after adjustment for cognitive and functional impairment. MD showed only a significant impact on incidence of dementia in Cox proportional hazards regression, but not in binary logistic regression models. Discussion The present study using different diagnostic measures of depression on future dementia found no clear significant associations of depression and incident dementia. Further in-depth investigation would help to understand the nature of depression in the context of incident dementia.
MUSTER: Improving protein sequence profile–profile alignments by using multiple sources of structure information

We develop a new threading algorithm MUSTER by extending the previous sequence profile–profile alignment method, PPA. It combines various sequence and structure information into single‐body terms which can be conveniently used in dynamic programming search: (1) sequence profiles; (2) secondary structures; (3) structure fragment profiles; (4) solvent accessibility; (5) dihedral torsion angles; (6) hydrophobic scoring matrix. The balance of the weighting parameters is optimized by a grading search based on the average TM‐score of 111 training proteins which shows a better performance than using the conventional optimization methods based on the PROSUP database. The algorithm is tested on 500 nonhomologous proteins independent of the training sets. After removing the homologous templates with a sequence identity to the target >30%, in 224 cases, the first template alignment has the correct topology with a TM‐score >0.5. Even with a more stringent cutoff by removing the templates with a sequence identity >20% or detectable by PSI‐BLAST with an E‐value <0.05, MUSTER is able to identify correct folds in 137 cases with the first model of TM‐score >0.5. Dependent on the homology cutoffs, the average TM‐score of the first threading alignments by MUSTER is 5.1–6.3% higher than that by PPA. This improvement is statistically significant by the Wilcoxon signed rank test with a P‐value < 1.0 × 10−13, which demonstrates the effect of additional structural information on the protein fold recognition. The MUSTER server is freely available to the academic community at http://zhang.bioinformatics. ku.edu/MUSTER. Proteins 2008. © 2008 Wiley‐Liss, Inc.
Improvement of the measurement update step of EKF-SLAM

In this study, the measurement update step of the Extended Kalman Filter (EKF)-based Simultaneous Localization and Mapping (SLAM) is improved. The computational complexity of the measurement uncertainty matrix inversion operation in the measurement update step is reduced via using Jacobi iteration method. It is observed that, the calculation of the measurement uncertainty matrix inverse by using Jacobi iteration method generates numerically more stable results than naive single and batch update operations. Moreover, it produces more accurate results than the results of Cholesky decomposition with less complexity.
Moving from interpretivism to critical realism in IS research: An exploration and supporting IT outsourcing example

The major contribution of the thesis Is to highlight the Importance of philosophical awareness In progressing research. It argues against the use of a pr/oritheory In research and proposes that an understanding of the philosophical underpinnings of particular research approaches can provide the opportunity to be ones own guide and to work out critically one's own conception of the world. It suggests that the adoption of critical realism as the underlying philosophical base can support research In a useful and practical manner. The thesis introduces the philosophy of critical reallsm and uses Its underlabouring role to provide new lnsights Into the Information systems arena in general and the case example In particular. The thesis specl! ically concentrates on a comparison between interpretlvism and critical realism, highlighting the differing approaches both have to research. The thesis provides an Illustrative case example examining the development of an organisation's first Information Business Plan and the subsequent outsourcing of the IS Department. The study was originally targeted at describing the Implementation of the organisation's first Information business plan but this changed as the information business plan Implementation was overtaken by events. It is argued that political directives from above were the major reason behind the organizational move to outsource all non-core activities, Including IS. The thesis documents a dissatisfaction with the ortglnallnterpretivtst approach on which the case Investigation was based and uses the case example to highlight the thesis arguments. Critical reallsm provldt:! s a promising analytical and explanatory framework for examining the Interplay between structure and agency within organizations. It Involves both Interpretive and explanatory understanding
Relationship Between Low‐Density Lipoprotein Cholesterol, Free Proprotein Convertase Subtilisin/Kexin Type 9, and Alirocumab Levels After Different Lipid‐Lowering Strategies

Background Alirocumab undergoes target‐mediated clearance via binding of proprotein convertase subtilisin/kexin type 9 (PCSK9). Statins increase PCSK9 levels; the effects of nonstatin lipid‐lowering therapies are unclear. Every‐4‐weeks dosing of alirocumab may be appropriate for some patients in absence of background statin but is not yet approved. Methods and Results Low‐density lipoprotein cholesterol (LDL‐C), PCSK9, and alirocumab levels were assessed in subjects (LDL‐C >130 mg/dL, n=24/group) after a 4‐week run‐in taking oral ezetimibe, fenofibrate, or ezetimibe placebo, when alirocumab 150 mg every 4 weeks (days 1, 29, and 57) was added. Maximal mean LDL‐C reductions from day −1 baseline (prealirocumab) occurred on day 71 in all groups: alirocumab plus placebo, 47.4%; alirocumab plus ezetimibe, 56.6%; and alirocumab plus fenofibrate, 54.3%. LDL‐C reductions were sustained through day 85 with alirocumab plus placebo (47.0%); the duration of effect was slightly diminished at day 85 versus day 71 with ezetimibe (49.6%) or fenofibrate combinations (43.2%). Free PCSK9 concentrations were lowest at day 71 in all groups, then increased over time; by day 85, free PCSK9 concentrations were higher, and alirocumab levels lower, with alirocumab plus fenofibrate, and to a lesser extent alirocumab plus ezetimibe, versus alirocumab plus placebo. Conclusions Alirocumab 150 mg every 4 weeks produced maximal LDL‐C reductions of 47% in combination with placebo and 54% to 57% in combination with ezetimibe or fenofibrate. The oral lipid‐lowering therapies appear to increase PCSK9 levels, leading to increased alirocumab clearance. Although the duration of effect was modestly diminished with alirocumab plus ezetimibe/fenofibrate versus placebo, the effect was less than observed in trials with background statins, and it would not preclude the use of alirocumab every 4 weeks in patients taking these nonstatin lipid‐lowering therapies concomitantly. Clinical Trial Registration URL: http://www.Clinicaltrials. gov. Unique identifier: NCT01723735.
Learning Finite-State Models for Language Understanding

Language Understanding in limited domains is here approached as a problem of language translation in which the target language is a formal language rather than a natural one. Finite-state transducers are used to model the translation process. Furthermore, these models are automatically learned from training data consisting of pairs of natural-language/formal-language sentences. The need for training data is dramatically reduced by performing a two-step learning process based on lexical/phrase categorization. Successful experiments are presented on a task consisting in the "understanding" of Spanish natural-language sentences describing dates and times, where the target formal language is the one used in the popular Unix command "at".
Broadband pricing strategies

Purpose – This article seeks to consider why broadband technologies have been so successful in reaching such a large number of new users so quickly, and what characteristics of its pricing have made this possible.Design/methodology/approach – Examines the different pricing strategies available, and their impact on broadband markets and prices, as well as some of the issues involved in measuring broadband prices.Findings – Pricing strategies have major implications for the future development of telecommunication markets, as they are dismantling the constructs on which telecommunication services have historically been priced (namely, distance, time and location). Broadband pricing strategies, especially the growing trend towards flat‐rate pricing, promise to transform the revenue streams and expansion of communication services in future.Originality/value – The findings, based on analysis of a unique price database across 145 countries, will be of value to operators and regulators.
Intermittent Renewables in the Next Generation Utility

Advances in digital communications and renewable energy technologies are poised to facilitate a transition to a “next generation utility” that fully integrates both supplyand demand-side resources in a way that can enable significantly larger penetrations of intermittent renewable energy technologies than conventionally thought possible. However, as the penetration of intermittent renewable energy grows, the variability of the resource becomes of increasing concern. This paper evaluates the potential reduction in variability due to the geographical dispersion of wind resources across large geographic areas. Specifically, the analysis uses data from within the Midwest Reliability Organization (MRO), the Southwest Power Pool (SPP), and the Electric Reliability Council of Texas (ERCOT). This analysis shows that there is a significant advantage to geographically distributing wind resources, even if individual sites do not exhibit large negative covariance. One of the primary advantages is the drastic reduction in time in which there is zero power production. Furthermore, all geographic regions show a reduction in portfolio variability compared to any individual site. The implication of this finding is that choosing locations for wind development in part based on benefits to system reliability can both decrease the cost of and likely increase the total amount of intermittent renewables that can be integrated on to an electric grid. Presented at PowerGen-RE 2008 conference & Exhibition, February 19-21 2008
Image classification using Hybrid MLP method

Content based image retrieval system is a research area which is growing very fast, here the query image's visual contents are used to search similar or exact images from a very large scale database of images. An effective system is proposed in our method in which both the semantically and visually relevant features are used for retrieval of the related images. For an efficient retrieval of image, it is necessary for a classification algorithm to be much efficient that it can find and locate the image at a different like in a compressed level. Our system proposes a novel training algorithm for Multi- Layer Perceptron Network to classify compressed images more efficiently. Here a hybrid MLP method is proposed for retrieval several features and shortens the semantic gap between low-level visual feature and high- level perception.
On the Radiative and Dynamical Feedbacks over the Equatorial Pacific Cold Tongue

Abstract An analysis of the climatic feedbacks in the NCAR Community Climate Model, version 3 (CCM3) over the equatorial Pacific cold tongue is presented. Using interannual signals in the underlying SST, the radiative and dynamical feedbacks have been calculated using both observations and outputs from the NCAR CCM3. The results show that the positive feedback from the greenhouse effect of water vapor in the model largely agrees with that from observations. The dynamical feedback from the atmospheric transport in the model is also comparable to that from observations. However, the negative feedback from the solar forcing of clouds in the model is significantly weaker than the observed, while the positive feedback from the greenhouse effect of clouds is significantly larger. Consequently, the net atmospheric feedback in the CCM3 over the equatorial cold tongue region is strongly positive (5.1 W m−2 K−1), while the net atmospheric feedback in the real atmosphere is strongly negative (−6.4 W m−2 K−1). A furt.
For Better and For Worse 1 Running head: COMPARISONS BETWEEN ROMANTIC PARTNERS For Better and For Worse: Everyday Social Comparisons between Romantic Partners

The authors examined the frequency, direction, and impact of social comparisons between romantic partners. Comparisons were expected to occur on a daily basis, due to regular interactions between partners. To the extent that one empathizes and shares outcomes with one’s partner, one might respond more positively to upward than downward comparisons. Study 1a was an experience-sampling study in which participants reported comparisons made to their spouse over two weeks. Study 1b examined reactions to the most significant comparisons made during the experience-sampling study. Participants reported making comparisons to their romantic partner more than once a day on average, and experienced more positive responses to upward than downward comparisons. Study 2 demonstrated that participants empathized and shared outcomes with their partner to a greater extent than with a friend. Study 3 confirmed that participants responded more positively to upward than downward comparisons even for domains high in self-relevance, and even when the comparison had negative self-evaluative implications. These results suggest that, due to higher levels of empathy and shared fate with partners, comparisons function differently in romantic than in other relationships.
Optoelectronic-Based Flexible Contact Sensor for Prosthetic Hand Application

This paper presents a flexible contact sensor for application on robotic fingers of prosthetic hand. The sensor is intended to provide contact sensing functionality when the finger is interacting with the environment. The sensor is based on optoelectronic infrared components mounted on a flexible substrate and connected by means of elastic electrical wires. The adopted configuration allows high sensitivities and fast responses. An important feature of the sensor is that the activation thresholds for contact sensing can be simply and precisely tuneable.
A Vehicle Detection Algorithm Based on Three-Frame Differencing and Background Subtraction

A vehicle detection algorithm based on three-frame differencing and background subtraction is presented in this paper. Firstly, improved GMM is for background subtraction, then the moving object region is gained using background subtraction, and then the background subtraction is combined with three-frame differencing to detect the motion information. The simulation results show that the proposed algorithm runs veraciously and can lower the false detection rate, and fits for real time detection.
Identifying Demonstrative Lovers in Tango Texting App

This paper aims at identifying the demonstrative lovers in Tango’s chat interface, i.e. the users sending each other romantic Tango Surprises. Our initial approach was to use a bag-of-words representation of the conversations as well as additional user features that we defined in cooperation with Tango operational team. We then conducted a SVM classification with a Linear Kernel, reaching 80% accuracy but a bias vs. variance diagnosis revealed that there was potential in increasing the model complexity. A SVM with a RBF Kernel gave us indeed better results, but with unacceptable computation time. Therefore, our second approach was to focus on an industrially operational solution, using only the conversations logs. The use of n-grams combined with optimized features normalization and selection enabled to build a program that could both accurately and efficiently identify demonstrative lovers based on their realtime conversations.
Adapting JML to generic types and Java 1.6

Despite the current effort to implement the Java Modeling Language for Java 1.5, and in particular for generic types, there has been no analysis of the effect of such a transition on JML itself, nor of what language changes should be implemented to take best advantage of the features of current Java. This paper analyzes the interactions between JML and the new features of Java 1.5 and 1.6, and it proposes appropriate changes to JML. Many implementation details for JML tools can be handled by choosing an existing Java 1.5+ compiler as a base; however, there are adjustments to the typing of JML expressions that would be appropriate, and there are issues needing careful attention arising from refinements, autoboxing, lock ordering operations, specification of enhanced for loops, type erasure, and the runtime execution of specifications involving type parameters. The features are implemented experimentally in OpenJML, an OpenJDK-based implementation of JML.
Incrementally updating a hybrid rule base based on empirical data

Abstract: Neurules are a kind of hybrid rules that combine a symbolic (production rules) and a connectionist (adaline unit) representation. One way that the neurules can be produced is from training examples/patterns, extracted from empirical data. However, in certain application fields not all of the training examples are available a priori. A number of them become available over time. In those cases, updating the neurule base is necessary. In this paper, methods for updating a hybrid rule base, consisting of neurules, to reflect the availability of new training examples are presented. They can be considered as a type of incremental learning method that retains the entire induced hypothesis and all past training examples. The methods are efficient, since they require the least possible retraining effort and the number of neurules produced is kept as small as possible. Experimental results that prove the above argument are presented.
Client State Management System Development Based on the Lightweight Java EE Architecture

The Java EE (Java Enterprise Edition, used to be called J2EE) platform is a multi-layer, distributed application framework that provides system level services to facilitate application development. However, classical Java EE architecture suffers poor performance for business applications due to its heavyweight EJB beans. This paper discusses the best practice of enterprise computing using the lightweight Java EE architecture and its applications in the development of a client state management system.
A framework to improve programmability of low power many-core processor for scalable DSP application

Embedded and ubiquitous sensors are driving industry to look for low power solutions for complex DSP algorithms; system engineers are also looking for upgradable capability to higher throughput and algorithm enhancements. Many-core, parallel architectures seem to be a solution to meet these interests at the same time. However it introduces a challenging problem: the programmability of a many-core processor is generally perceived by industry as difficult and inefficient. A new framework is proposed to solve this challenge. This framework includes a dataflow programming methodology at the top level design, and an embedded automatic cell generator to solve the module level data parallel problem. Data flow programming methodologies avoid explicit synchronization among modules; the data flow naturally drives the synchronization. At the module level, a cell generator handles application-specifics, including data dependencies, amount of parallelization required to achieve desired throughput and complete memory management, and generation of a library. This framework provides a path to quickly develop a DSP algorithm on a many-core processor, to achieve a scalable, higher throughput, and lower power solution. The framework demonstrated by this paper has been applied to various DSP algorithms to efficiently parallelize and scale for different through-put or power requirement, on Coherent Logix's low-power 100 core hx3100TM processor based on HyperXTM technology.