Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring the Euro-Dollar Permanent Equilibrium Exchange Rate using the Unobserved Components Model

This paper employs an unobserved component model that incorporates a set of economic fundamentals to obtain the Euro-Dollar permanent equilibrium exchange rates (PEER) for the period 1975Q1 to 2008Q4. The results show that for most of the sample period, the Euro-Dollar exchange rate closely followed the values implied by the PEER. The only significant deviations from the PEER occurred in the years immediately before and after the introduction of the single European currency. The forecasting exercise shows that incorporating economic fundamentals provides a better long-run exchange rate forecasting performance than a random walk process.
A general framework for multi-accent Mandarin speech recognition using adaptive neural networks

In this paper, we propose a general framework for multi-accent speech recognition that combines Multi-level Adaptive Network (MLAN) and automatic model selection system based on accent classification. This framework solves the problem of domain mismatch between standard Mandarin and accent data and makes full use of limited accent data. The effectiveness of the proposed method was evaluated on two typical Chinese accent data, namely Shanghai and Chongqing accents. Results show higher performance of the framework on multi-accent speech recognition compared to GMM-HMM systems with prior accent label knowledge, with up to 3.89% CER (Character Error Rate) reduction on Chongqing accent test set and 1.71% on Shanghai accent test set.
The δ Subunit of γ-Aminobutyric Acid Type A Receptors Does Not Confer Sensitivity to Low Concentrations of Ethanol

GABAA receptors (GABAARs) are usually formed by α, β, and γ or δ subunits. Recently, δ-containing GABAARs expressed in Xenopus oocytes were found to be sensitive to low concentrations of ethanol (1–3 mM). Our objective was to replicate and extend the study of the effect of ethanol on the function of α4β3δ GABAARs. We independently conducted three studies in two systems: rat and human GABAARs expressed in Xenopus oocytes, studied through two-electrode voltage clamp; and human GABAARs stably expressed in the fibroblast L(tk–) cell line, studied through patch-clamp electrophysiology. In all cases, α4β3δ GABAARs were only sensitive to high concentrations of ethanol (100 mM in oocytes, 300 mM in the cell line). Expression of the δ subunit in oocytes was assessed through the magnitude of the maximal GABA currents and sensitivity to zinc. Of the three rat combinations studied, α4β3 was the most sensitive to ethanol, isoflurane, and 5α-pregnan-3α,21-diol-20-one (THDOC); α4β3δ and α4β3γ2S were very similar in most aspects, but α4β3δ was more sensitive to GABA, THDOC, and lanthanum than α4β3γ2S GABAARs. Ethanol at 30 mM did not affect tonic GABA-mediated currents in dentate gyrus reported to be mediated by GABAARs incorporating α4 and δ subunits. We have not been able to replicate the sensitivity of α4β3δ GABAARs to low concentrations of ethanol in four different laboratories in independent studies. This suggests that as yet unidentified factors may play a critical role in the ethanol effects on δ-containing GABAARs.
Batch heterogeneous outlier rejection for feature-poor SLAM

In this paper, the problem of outliers in a batch alignment problem (given heterogeneous measurements and sparse features) is considered. The conventional approach from the field of computer vision, pairwise RANSAC, is shown to be inappropriate for this scenario, which motivates the need for a new method. To address this problem, the heterogeneous measurements are compared in a common currency using their respective scaled measurement innovations. Furthermore, a family of three algorithms for classifying outliers given a hypothesis model are presented, each having its own balance between speed and accuracy. These classification criteria are then incorporated through iterative reclassification in a batch alignment framework, providing a robust estimate for localization and mapping. Lastly, statistical validation is obtained through a large set of simulated trials.
Toward a Formal Characterization of Real-World General Intelligence

Two new formal definitions of intelligence are presented, the ”pragmatic general intelligence” and ”efficient pragmatic general intelligence. ” Largely inspired by Legg and Hutter’s formal definition of ”universal intelligence,” the goal of these definitions is to capture a notion of general intelligence that more closely models that possessed by humans and practical AI systems, which combine an element of universality with a certain degree of specialization to particular environments and goals. Pragmatic general intelligence measures the capability of an agent to achieve goals in environments, relative to prior distributions over goal and environment space. Efficient pragmatic general intelligences measures this same capability, but normalized by the amount of computational resources utilized in the course of the goal-achievement. A methodology is described for estimating these theoretical quantities based on observations of a real biological or artificial system operating in a real environment. Finally, a measure of the ”degree of generality” of an intelligent system is presented, allowing a rigorous distinction between ”general AI” and ”narrow AI. ”
Segment gating for static energy reduction in networks-on-chip

Chip multiprocessors (CMPs) have emerged as a primary vehicle for overcoming the limitations of uniprocessor scaling, with power constraints now representing a key factor of CMP design. Recent studies have shown that the on-chip interconnection network (NOC) can consume as much as 36% of overall chip power. To date, researchers have employed several techniques to reduce power consumption in the network, including the use of on/off links by means of power gating. However, many of these techniques target dynamic power, and those that consider static power focus exclusively on flit buffers. In this paper, we aim to reduce static power consumption through a comprehensive approach that targets buffers, switches, arbitration units, and links. We establish an optimal power-down scheme which we use as an upper bound to evaluate several static policies on synthetic traffic patterns. We also evaluate dynamic utilization-aware power-down policies using traces from the PARSEC benchmark suite. We show that both static and dynamic policies can greatly reduce static energy at low injection rates with only minimal increases in dynamic energy and latency.
Specific Association of Lectin LecB with the Surface of Pseudomonas aeruginosa: Role of Outer Membrane Protein OprF

The fucose binding lectin LecB affects biofilm formation and is involved in pathogenicity of Pseudomonas aeruginosa. LecB resides in the outer membrane and can be released specifically by treatment of an outer membrane fraction with fucose suggesting that it binds to specific ligands. Here, we report that LecB binds to the outer membrane protein OprF. In an OprF-deficient P. aeruginosa mutant, LecB is no longer detectable in the membrane but instead in the culture supernatant indicating a specific interaction between LecB and OprF.
Multi-parent insertion crossover for vehicle routing problem with time windows

Multi parent crossover has been successfully applied to solve many combinatorial optimization problems such as unconstrained binary quadratic programming problem (UBQP). This because using more than two parents has increased the intensification process by exploiting the information shared by multi parents. However not all type of crossovers are suitable to solve vehicle routing problem (VRP). Therefore, this work introduces a multi parent insertion crossover in solving vehicle routing problem with time windows (VRPTW) by enhancing two parent insertion crossovers. This crossover exchange information among three parents instead of two. Result tested on Solomon VRPTW benchmarks demonstrate that multi parent crossover outperformed two parent crossover on same instances. This prove the effectiveness of having more parents for crossover that can be help the search to find better quality solution.
Incretin-Based Therapies for the Treatment of Type 2 Diabetes: Evaluation of the Risks and Benefits

Type 2 diabetes is a complex metabolic disorder characterized by hyperglycemia arising from a combination of insufficient insulin secretion together with resistance to insulin action. The incidence and prevalence of type 2 diabetes are rising steadily, fuelled in part by a concomitant increase in the worldwide rates of obesity. As longitudinal studies of type 2 diabetes provide evidence linking improved glycemic control with a reduction in the rates of diabetes-associated complications, there is considerable interest in the therapy of type 2 diabetes (Fig. 1), with a focus on the development and use of new agents that exhibit improved efficacy and safety relative to current available medicines. Figure 1 Relative comparison of properties exhibited by different classes of agents approved for the treatment of type 2 diabetes. CVD, cardiovascular disease; TG, triglycerides; CHF, congestive heart failure. A1C reduction depends on starting A1C. Although the number of patients with type 2 diabetes that successfully achieve target levels of A1C is steadily improving, a substantial number of subjects continue to fall short of acceptable treatment goals, leaving them at high risk for development of diabetes-associated complications (1). More importantly, a large number of subjects with type 2 diabetes fail to achieve target values for glucose, lipids, and blood pressure, with only 12.2% of patients meeting target values despite recent improvements in therapeutic agents targeting hyperglycemia, dyslipidemia, and hypertension (2). The development of multiple new agents for the treatment of type 2 diabetes has broadened the options for patient-specific therapy. However, no currently available agents exhibit the ideal profile of exceptional glucose-lowering efficacy to safely achieve target levels of glycemia in a broad range of patients. Hence, highly efficacious agents that exhibit unimpeachable safety, excellent tolerability, and ease of administration to ensure long-term adherence and that also clearly reduce common comorbidities and complications of diabetes are …
Naturally Occurring Plant Phenols Formation in Epidermis and Lungs of SENCAR Mice by Inhibition of Polycyclic Aromatic Hydrocarbon-DNA Adduct Updated

Naturally occurring plant phenols such as tannic acid, quercetin, myricetin, and anthraflavic acid are known to inhibit the mutagenicity of several bay-region diol-epoxides of polycyclic aromatic hydrocarbons (PAHs). The binding of bay-region diol-epoxides of PAHs to target tissue DNA is thought to be essential for the initiation of cancer by these compounds. In this study we investigated the effect of these plant phenols on PAH-DNA adduct formation in the epidermis and lung of SENCAR mice. In vitro addition of tannic acid, quercetin, myricetin, and anthrafla vic acid (25 Â¿IM) to an incubation system containing epidermal microsomes prepared from either control or 3-methylcholanthrene-pretreated mice inhibited benzo(a)pyrene binding to calf thymus DNA by 63-64, 38-43, 36-37, and 27-33%, respectively. A single topical application of tannic acid, quercetin, myricetin, and anthraflavic acid at a dose of 400 nmol/ kg body weight resulted in the inhibition of |'I I|hcn/o(u)p\rene binding to epidermal DNA (48-73%) and protein (51-63%). The same dose of these plant phenols (400 /tmol/kg) caused even greater inhibition of (Â±> [3H]-7/3,8a-dihydroxy-7,8-dihydrobenzo(a)pyrene and |3H]-7,12-dimethylbenz(<z)anthracene binding to epidermal DNA and protein. The for mation of (+) -7j8,8a dihydroxy 9a,10a epoxy 7,8,9,10 tetrahydrobenzo(a)pyrene-deoxyguanosine adducts was substantially diminished in both epidermis (62-86%) and lungs (38-84%). These results indicate that tannic acid, quercetin, myricetin, and anthraflavic acid are potent inhibitors of carcinogen binding to epidermal and lung DNA and suggest that these plant phenols could prove useful in modifying the risk of tumor induction by PAHs such as benzo(<i)pyrene and 7,12-dimethylbenz(a)anthrar.ene in these two tissues.
Magnetic Resonance Imaging of Changes in Muscle Tissues after Membrane Trauma

Abstract: A pure electroporation injury leads to cell membrane disruption and subsequent osmotic swelling of the tissue. The state of water in the injured area of a tissue is changed and differs from a healthy tissue. Magnetic resonance imaging (MRI), which is very sensitive to the quality of the interaction between mobile (water) protons and a restricted (protein) proton pool, is therefore a useful tool to characterize this injury. Here, we present a protocol designed to measure the difference between the values of the transverse magnetic relaxation time (T2) in MRIs of healthy and electrically injured tissue. In addition, we present a method to evaluate the two main contributions to the MRI contrast, the degree of structural alteration of the cellular components (including a major contribution from membrane pores), and edema. The approach is useful in assessing the level of damage that electric shocks produce in muscle tissues, in that edema will resolve in time whereas structural changes require active repair mechanisms.
Comparative Analysis of Predictive Techniques for Release Readiness Classification

Context: A software release is the deployment of a version of an evolving software product. Product managers are typically responsible for deciding the release content, time frame, price, and quality of the release. Due to all the dynamic changes in the project and process parameters, the decision is highly complex and of high impact.Objective: This paper has two objectives: i) Comparative analysis of predictive techniques in classifying an ongoing release in terms of its expected release readiness. , and ii) Comparative analysis between regular and ensemble classifiers to classify an ongoing release in terms of its expected release readiness.Methodology: We use machine learning classifiers to predict release readiness. We analyzed three OSS projects under Apache Software Foundation from JIRA issue repository. As a retrospective study, we covered a period of 70 months, 85 releases and 1696 issues. We monitored eight established variables to train classifiers in order to predict whether releases will be ready versus non-ready. Predictive performance of different classifiers was compared by measuring precision, recall, F-measure, balanced accuracy, and area under the ROC curve (AUC). Results: Comparative analysis among nine classifiers revealed that ensemble classifiers significantly outperform regular classifiers. Balancing precision and recall, Random Forrest and BaggedADABoost were the two best performers in total, while Naïve Bayes performed best among just the regular classifiers.
The resolution property for schemes and stacks

Abstract We prove the equivalence of two fundamental properties of algebraic stacks: being a quotient stack in a strong sense, and the resolution property, which says that every coherent sheaf is a quotient of some vector bundle. Moreover, we prove these properties in the important special case of orbifolds whose associated algebraic space is a scheme.
Preface the Aicte Series (volumes 1 through 6): a Recap of Previous Editions

Over the past six years, the AICTE series has introduced a number of instructional pedagogies steeped in technology and dedicated to furthering the study of teaching and learning with technology and its practical applications in the classroom. Focus Areas. In the inaugural Volume 1, Integrating Information and Communications Technologies into the Classroom, published in 2007, we addressed the multiple perspectives of teaching and learning with technology and promoting research efforts, positions, and practices advancing the state-of-the-art application of technology in formal education, corporate training, higher education, professional development, and proprietary education. Volume 1 focused on contributions from many disciplines of educational and instructional technology and discussed specific focus areas of: business, computer science , and information technology, distance learning technology education, communications technologies employed in the classroom, and technology as a teaching strategy and learning style. Models for Effective Education. Adapting Information and Communication for Effective Education, Volume 2 (2008), introduced a series of models for consideration that included the Teacher (Teach-Understand-Integrate) model for faculty development; the Blended ICT Model for higher education; the
Characterizing Model Errors and Di erencesStephen

A critical component of applying machine learning algorithms is evaluating the performance of the models induced and using the evaluation to guide further development. Traditionally the most common evaluation metric is error or loss, however this provides very little information for the designer to use when constructing a system. We argue that an evaluation method should provide detailed feedback on the performance of an algorithm and that this feedback should be in the language of the problem: Our goal is to characterize model errors or the diierences between models in the feature space. We provide a framework for this that allows diier-ent algorithms to be used as the discovery engine and we consider two approaches: (1) a classiication strategy where we use a standard rule learner such as C5; (2) a descriptive paradigm where we use a new discovery algorithm: a contrast set miner. We show that C5 suuers from several problems that make it unsuitable for this task.
Dwq : Esprit Long Term Research Project, No 22469 Modeling Multidimensional Databases: a Formal Object-centered Approach Foundations of Data Warehouse Quality Modeling Multidimensional Databases: a Formal Object-centered Approach

In this paper, we propose a formal framework based on description logics as a basis for both modeling multidimensional databases at the conceptual level and understanding related reasoning problems and services. Description logics are well-understood, object-centered formalisms which have already proved their suitability as a unifying framework for object-centered representation formalisms. We extend a description logic with new constructors which allow to define operators on cubes. The constructors we propose correspond in part to the operators on data cubes given in (Agrawal&al 1997).
Mining Frequent Itemsets for data streams over Weighted Sliding Windows

In this paper, we propose a new framework for data stream mining, called the weighted sliding window model. The proposed model allows the user to specify the number of windows for mining, the size of a window, and the weight for each window. Thus, users can specify a higher weight to a more significant data section, which will make the mining result closer to user’s requirements. Based on the weighted sliding window model, we propose a single pass algorithm, called WSW(Weighted Sliding Window mining), to efficiently discover all the frequent itemsets from data streams. By analyzing data characteristics, an improved algorithm, called WSW-Imp, is developed to further reduce the time of deciding whether a candidate itemset is frequent or not. Empirical results show that WSW-Imp outperforms WSW under the weighted sliding windows.
Mathematical modeling and parameter estimation of blood pressure oscillometric waveform

In this paper, a mathematical model for the blood pressure oscillometric waveform (OMW) is developed and a statespace approach using the extended Kalman filter (EKF) is proposed to adaptively estimate and track parameters of clinical interest. The OMW model is driven by a previously proposed pressure-lumen area model of the artery under the deflating cuff. The arterial lumen area is a function of vessel properties, the cuff pressure, and the arterial pressure. Over the deflation period, the arterial pressure causes lumen area oscillations while the deflating cuff pressure adds a slow-varying component to these oscillations. In the previous literature, it has been demonstrated that the oscillometric pulses are proportional to the arterial area oscillations. In this paper, the OMW is modeled as the difference between the whole lumen area model and the slow-varying component of the lumen area caused by the deflating cuff pressure. The OMW model is then represented in the statespace and the extended Kalman filter (EKF) is incorporated to estimate and track the time-varying model parameters during the cuff deflation period. The parameter tracking performance of the EKF is evaluated on a simulated noisy OMW.
A Multicenter, Phase II, Randomized, Noncomparative Clinical Trial of Radiation and Temozolomide with or without Vandetanib in Newly Diagnosed Glioblastoma Patients

Purpose: Vandetanib, a tyrosine kinase inhibitor of KDR (VEGFR2), EGFR, and RET, may enhance sensitivity to chemotherapy and radiation. We conducted a randomized, noncomparative, phase II study of radiation (RT) and temozolomide with or without vandetanib in patients with newly diagnosed glioblastoma (GBM). Experimental Design: We planned to randomize a total of 114 newly diagnosed GBM patients in a ratio of 2:1 to standard RT and temozolomide with (76 patients) or without (38 patients) vandetanib 100 mg daily. Patients with age ≥ 18 years, Karnofsky performance status (KPS) ≥ 60, and not on enzyme-inducing antiepileptics were eligible. Primary endpoint was median overall survival (OS) from the date of randomization. Secondary endpoints included median progression-free survival (PFS), 12-month PFS, and safety. Correlative studies included pharmacokinetics as well as tissue and serum biomarker analysis. Results: The study was terminated early for futility based on the results of an interim analysis. We enrolled 106 patients (36 in the RT/temozolomide arm and 70 in the vandetanib/RT/temozolomide arm). Median OS was 15.9 months [95% confidence interval (CI), 11.0–22.5 months] in the RT/temozolomide arm and 16.6 months (95% CI, 14.9–20.1 months) in the vandetanib/RT/temozolomide (log-rank P = 0.75). Conclusions: The addition of vandetanib at a dose of 100 mg daily to standard chemoradiation in patients with newly diagnosed GBM or gliosarcoma was associated with potential pharmacodynamic biomarker changes and was reasonably well tolerated. However, the regimen did not significantly prolong OS compared with the parallel control arm, leading to early termination of the study. Clin Cancer Res; 21(16); 3610–8. ©2015 AACR.