Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach to Large Margin Design of Prototype-Based Pattern Classifiers

In this paper, we propose a maximum separation margin (MSM) training method for multiple-prototype (MP)-based pattern classifiers in which a sample separation margin defined as the distance from the training sample to the classification boundary can be calculated precisely. Similar to support vector machine (SVM) methodology, MSM training is formulated as a multicriteria optimization problem which aims at maximizing the separation margin and minimizing the empirical error rate on training data simultaneously. By making certain relaxation assumptions, MSM training can be reformulated as a semidefinite programming (SDP) problem that can be solved efficiently by some standard optimization algorithms designed for SDP. Evaluation experiments are conducted on the task of the recognition of most confusable Kanji character pairs identified from popular Nakayosi and Kuchibue handwritten Japanese character databases. It is observed that the MSM-trained MP-based classifier achieves a similar character recognition accuracy as that of the state-of-the-art SVM-based classifier, yet requires much fewer classifier parameters.
‘A different kind of normal’: parents’ experiences of early care and education for young children born prematurely

ABSTRACT The number of preterm births is increasing globally and in England, yet professional knowledge about the short- and long-term developmental consequences and the psycho-social effect on parents is limited amongst the early years workforce. Using a social-ecological systems theory approach, this paper reports on a mixed-methods study that aimed to explore parents’ experiences of early care and education for young children born prematurely. Findings suggest that having a baby born prematurely has the potential to have a detrimental effect on parent–child bonding and can lead to post-traumatic stress disorder for parents. Parents identified a need for professional training for early years practitioners and teachers to help them understand the concept of ‘corrected age’ and the extra support that children born prematurely (and their parents) might need in attending parent and toddler groups, early years settings and on transition to school, especially if there are also multiple births.
Dual Dijkstra Search for paths with different topologies

This paper describes a new search algorithm, the Dual Dijkstra Search. From a given initial and final configuration, Dual Dijkstra Search finds various paths which have different topologies simultaneously. This algorithm allows you to enumerate not only the optimal one but variety of meaningful candidates among local minimum paths. It is based on the algorithm of Dijkstra, which is popularly used to find an optimal solution. The method consists of two procedures: First computes local minima and ranks the paths in order of optimality. Then classify them with their topological properties and take out only the optimal paths in each groups. Computed examples include generating collision-free motion along 2D space and motion planning of 3-DOF robot. We also proposed the idea of motion compression, which simplifies the high dimensional motion planning problem. Together with this idea, we applied Dual Dijkstra Search to 7-DOF arm manipulation problem and succeeded in obtaining variety of motion candidates.
Drug-Induced Nephrotoxicity and Dose Adjustment Recommendations: Agreement Among Four Drug Information Sources

Hospitalized patients require the use of a variety of drugs, many of which individually or in combination have the potential to cause kidney damage. The use of potentially nephrotoxic drugs is often unavoidable, and the need for dose adjustment should be evaluated. This study is aimed at assessing concordance in information on drug-induced nephrotoxicity and dose adjustment recommendations by comparing four drug information sources (DRUGDEX®, UpToDate®, Medscape® and the Brazilian Therapeutic Formulary) using the formulary of a Brazilian public hospital. A total of 218 drugs were investigated. The global Fleiss’ kappa coefficient was 0.265 for nephrotoxicity (p < 0.001; CI 95%, 0.211–0.319) and 0.346 for recommendations (p < 0.001; CI 95%, 0.292–0.401), indicating fair concordance among the sources. Anti-infectives and anti-hypertensives were the main drugs cited as nephrotoxic by the different sources. There were no clear definitions for qualitative data or quantitative values for dose adjustments among the four information sources. There was no advice for dosing for a large number of the drugs in the international databases. The National Therapeutic Formulary offered imprecise dose adjustment recommendations for many nephrotoxic drugs. Discrepancies among information sources may have a clinical impact on patient care and contribute to drug-related morbidity and mortality.
Distributed knowledge extracted by a mas using ontology alignment methods

Nowadays new product development involves different types of actors (technician, managers, board of directors) which must be able to share knowledge, experiences and work together efficiently. Each actor has a professional specialty and uses one or several software tools (CAO, project management tools, PLM tools .) dedicated to her specific activities. Each of these software tools produces different information sources (databases, XML files, text files) which are distributed through the enterprise network. In this paper, we present the design of a multi-agent software architecture that allows the capitalization of distributed and heterogeneous knowledge. We then describe how the agents assist users to create domain ontologies matching with professional software tools databases and how the agent build semantic queries to extract knowledge.
Exploring Adolescents’ Experiences and Parents’ Teaching Strategies Related to Food Preparation Literacy: A Photovoice and Grounded Theory Approach

s screened (n =882) Records excluded (n = 695) Full-text articles assessed for eligibility (n = 187) Full-text articles excluded, with reasons (n = 149) Studies included in synthesis (n = 38) Studies included in quantitative synthesis (n = 20) Studies included in qualitative synthesis (n = 15) Studies included in Mixed-Methods synthesis (n = 3)
Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks

Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with very short utterances (∼3s). In this contribution we present an open-source, end-to-end, LSTM RNN system running on limited computational resources (a single GPU) that outperforms a reference i-vector system on a subset of the NIST Language Recognition Evaluation (8 target languages, 3s task) by up to a 26%. This result is in line with previously published research using proprietary LSTM implementations and huge computational resources, which made these former results hardly reproducible. Further, we extend those previous experiments modeling unseen languages (out of set, OOS, modeling), which is crucial in real applications. Results show that a LSTM RNN with OOS modeling is able to detect these languages and generalizes robustly to unseen OOS languages. Finally, we also analyze the effect of even more limited test data (from 2.25s to 0.1s) proving that with as little as 0.5s an accuracy of over 50% can be achieved.
Implementing an interface to networked services

This paper highlights the general problems and difficulties in using networked services. A prototype has been developed to help users interact with networked services. General design principles which arise in implementing a prototype user interface to networked services are discussed. The construction of the prototype is based on an object-oriented approach. The way it communicates with networked services and a help facility are also described.
Estimating Two-Stage Network Technology Inefficiency: An Application to Cooperative Shinkin Banks in Japan

The authors model the performance of DMUs (decision-making units) using the directional distance function within a two-stage framework. In the first stage of production, DMUs use inputs to produce an intermediate output. In stage 2, the intermediate output is used to produce final outputs. In contrast to DEA (data envelopment analysis) models, the two-stage directional model accounts for a network production structure and allows non-radial scaling of outputs and inputs. An empirical application of the method is provided for Japanese credit cooperative Shinkin banks. These banks use labor, physical capital, equity capital in a first stage to produce deposits, and then use the deposits to produce loans, securities investments, and other interest bearing assets in a second stage. The authors find evidence of greater inefficiency in the first stage of production than in the second stage of production. In addition, the findings indicate that models that ignore a network structure and measure performance using a black-box DEA model miss about 50% of total bank inefficiency when measured by the network model.
An Exponential Time/Space Speedup For Resolution

Satisfiability algorithms have become one of the most practi cal and successful approaches for solving a variety of real-world problems, including hardware verifi cation, experimental design, planning and diagnosis problems. The main reason for the success is due to highly optimized algorithms for SAT based on resolution. The most successful of these is clause learning, a DPLL scheme based on caching intermediate clauses that are “learned” throughout the backtrack search procedure. The main bottleneck to this approach is space, and thus there has been a tremendous amount of research aimed at identifying good heuristics for deciding what information to cache. Haken first suggested a formal approach to this issue, and Ben-Sasson [3] posed the question of whether there is a time/space tradeoff for resolution. Our main result is an optimal time/space tradeoff for resolution. Namely, we present an infinite family of propositional formulas whose minimal space proofs all have exponential time, but if just three extra units of storage are allowed, then the formulas can be proved in linear time. We also prove another related theorem. Given an unsatisfiabl e formula F and an integer k, the resolution space problem is to determine if F has a resolution proof which can be verified using space k. We prove that this problem is PSPACE complete.
The Berne OECD Workshop on Productivity Analysis and Measurement: Conclusions and Future Directions

“For the calculation of aggregate quantity or volume change of inputs and outputs, an index formula must be selected. In the standard growth accounting approach the index formula corresponds to a certain specification of the production function and TFP change represents technological change. However, such an approach depends on strong (neo-classical) assumptions, for instance that production processes are subject to constant returns to scale and that there is perfect competition. We don’t wish to make such strong assumptions, and prefer to select an index formula on the basis of its properties. ” Dirk van den Bergen, Myriam van Rooijen-Horsten, Mark de Haan and Bert M. Balk (2006; 3).
Genetic Programming as Alternative for Predicting Development Effort of Individual Software Projects

Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained from a genetic programming model was compared against one generated from the application of a statistical regression model. A sample of 219 projects developed by 71 practitioners was used for generating the two models, whereas another sample of 130 projects developed by 38 practitioners was used for validating them. The models used two kinds of lines of code as well as programming language experience as independent variables. Accuracy results from the model obtained with genetic programming suggest that it could be used to predict the software development effort of individual projects when these projects have been developed in a disciplined manner within a development-controlled environment.
Perpetual: Byzantine Fault Tolerance for Federated Distributed Applications

Modern distributed applications rely upon the functionality of services from multiple providers. Mission-critical services, possibly shared by multiple applications, must be replicated to guarantee correct execution and availability in spite of arbitrary (Byzantine) faults. Furthermore, shared services must enforce strict fault isolation policies to prevent cascading failures across organizational and application boundaries. Most existing protocols for Byzantine fault-tolerant execution do not support interoperability between replicated services while others provide poor fault isolation. Moreover, existing protocols place impractical limitations on application development by disallowing long-running threads of computation, asynchronous operation invocation, and asynchronous request processing. We present Perpetual, a protocol that facilitates unrestricted interoperability between replicated services while enforcing strict fault isolation criteria. Perpetual supports both asynchronous operation invocation and asynchronous request processing. Perpetual also supports long-running threads of computation, enabling Byzantine fault-tolerant execution of services that carry out active computations. We present performance evaluations demonstrating a moderate overhead due to replication. Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Perpetual: Byzantine Fault Tolerance for Federated Distributed Applications Sajeeva L. Pallemulle Haraldur D. Thorvaldsson Kenneth J. Goldman Department of Computer Science and Engineering Washington University in St. Louis, St. Louis, MO 63130 USA {sajeeva, harri, kjg}@cse.wustl. edu
The Temperature-Compensated Goodwin Model Simulates Many Circadian Clock Properties

Goodwin's model oscillator, which consists of a negative feedback loop within a single gene expression pathway (1963, 1965), was modified in order to demonstrate temperature compensation, a characteristic property of circadian oscillators. Temperature effects were introduced into the oscillatory mechanism by means of the Arrhenius equation. This term may provide a simplified estimate of the complicated temperature-dependence of actual cellular processes. Temperature compensation within the oscillatory mechanism was achieved by balancing the effect of different temperatures on amplifying processes and on stabilizing processes (antagonistic balance; Ruoff, 1994). Apart from temperature compensation, the modified Goodwin oscillator showed other characteristic properties of circadian clocks including: (i) temperature entrainment even by temperature cycles of rather low amplitude (1 °C), (ii) phase shifts by temperature pulses or steps of different signs (up or down) and different amplitudes, giving rise to phase response curves similar to those reported, for example, inNeurospora crassa(Francis & Sargent 1979; Rensinget al., 1987; Nakashima, 1987). A single change in one of the reaction rates of the model oscillator not only caused a change in the period length but also abolished temperature compensation. This closely corresponds to the effects observed after a single point mutation of the clock gene (frq7) inNeurospora crassa(Aronsonet al., 1994b). Limit cycle oscillations were damped at permanently low temperatures, however the period of the damped oscillations was still temperature compensated.
Association of Cholesterol Efflux Capacity With Clinical Features of Metabolic Syndrome: Relevance to Atherosclerosis

Background The contribution of high‐density lipoprotein to cardiovascular benefit is closely linked to its role in the cellular cholesterol efflux process; however, various clinical and biochemical variables are known to modulate the overall cholesterol efflux process. The aim of this study was to evaluate the extent to which clinical and biological anomalies associated with the establishment of the metabolic syndrome modulate cholesterol efflux capacity and contribute to development of atherosclerosis. Methods and Results This study involved patients (n=1202) displaying atherogenic dyslipidemia in primary prevention who were referred to our prevention center. Among these patients, 25% presented at least 3 criteria of the metabolic syndrome, as defined by the National Cholesterol Education Program Adult Treatment Panel III. We measured the capacity of 40‐fold diluted serum to mediate cholesterol efflux from cholesterol‐loaded human THP‐1 macrophages. Cholesterol efflux capacity was reduced progressively by 4% to 11% (P<0.0001) as a function of the increasing number of coexisting criteria for the metabolic syndrome from 1 to 5. This observation was primarily related to reductions in scavenger receptor class B member 1 and ATP binding cassette subfamily G member 1–dependent efflux. Multivariate analyses indicate that serum efflux capacity was significantly associated with established metabolic syndrome (odds ratio 0.45; 95% CI 0.28–0.72; P=0.009) independent of age, low‐density lipoprotein cholesterol, status with regard to lipid‐lowering therapy, smoking status, and alcohol consumption. Conclusions Our study revealed that individual criteria of metabolic syndrome are closely related synergistically to cholesterol efflux capacity. In addition, established metabolic syndrome and cholesterol efflux capacity were independently associated with clinical features of atherosclerosis.
The science of pterygia

Pterygium is an ocular surface disease of humans attributed to chronic ultraviolet-B exposure. Clinically, the condition involves invasive centripetal growth with associated inflammation and neovascularisation. Previous clinical studies focused primarily on the clinical characteristics and surgical management of pterygia and, because of this, the pathogenesis of pterygia remains incompletely understood. However, considerable progress in this area has been achieved, providing additional insight into this complex disease. This recent evidence implicates antiapoptotic mechanisms, immunological mechanisms, cytokines, growth factors, extracellular matrix modulators, genetic factors, viral infections and other possible causative factors. Limited investigation regarding differences in pathogenesis of primary and recurrent pterygia has been performed. We summarise many of these recent discoveries concerning the pathogenesis of pterygia and describe reported differences between primary and recurrent pterygia.
Injecting SMS Messages into Smart Phones for Security Analysis

The Short Message Service (SMS) is one of the building blocks of the mobile phone service. It is used for text messaging by users as well as for services that work under the hood of every mobile phone. The security of SMS-implementations is critical because attacks can be carried out remotely without any user interaction and because SMS can not be disabled or filtered on current mobile phones. This paper presents a novel method for vulnerability analysis of SMS-implementations. The presented approach is independent from any service operator, does not produce costs, and guarantees reproducible results. Our approach was able to identify previously unknown security flaws that can be used for Denial-of-Service attacks against current smart phones.
Interaction of HDL cholesterol concentrations on the relationship between physical function and inflammation in community-dwelling older persons.

BACKGROUND the existence of a relationship among inflammation, high-density lipoprotein cholesterol (HDL-C) and physical function has been suggested. OBJECTIVE the aim of the study is to investigate the possible interaction of HDL-C on inflammation and physical function. DESIGN cross-sectional study. SETTING town of Tuscania (Italy). SUBJECTS all the 329 community-dwelling older persons aged > or =75 years (mean age 79.8 +/- 5.2 years, women 56.2%). METHODS HDL-C, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) and interleukin-6 (IL-6) were measured. Activities of daily living (ADL), instrumental ADL (IADL) and 4-m walking speed were assessed. Linear regression models were performed. RESULTS given the multiple significant interactions, models were stratified according to HDL-C concentrations. In participants with normal HDL-C concentrations, only IL-6 showed a significant association with IADL (beta = -0.439, SE = 0.176, P = 0.01). In participants with low HDL-C concentrations, all three inflammatory biomarkers were significantly associated with 4-m walking speed and IADL. IL-6 was also significantly associated with ADL (beta = -0.755, SE = 0.259, P = 0.006), whereas borderline significances were reported for CRP and ESR. CONCLUSIONS the association between inflammation and physical function is particularly enhanced in elders with low HDL-C concentrations. Though HDL-C may merely act as a wellbeing index, HDL-C concentrations should be considered in studies evaluating inflammation and physical function.
Predicting neurosurgical outcomes in focal epilepsy patients using computational modelling

See Eissa and Schevon (doi:10.1093/aww332) for a scientific commentary on this article. Surgery can be a last resort for patients with intractable, medically refractory epilepsy. For many of these patients, however, there is substantial risk that the surgery will be ineffective. The prediction of who is likely to benefit from a surgical approach is crucial for being able to inform patients better, conduct principled prospective clinical trials, and ultimately tailor therapeutic approaches to these patients more effectively. Dynamical computational models, informed with patient data, can be used to make predictions and give mechanistic insight. In this study, we develop patient-specific dynamical network models of epileptogenic cortex. We infer the network connectivity matrix from non-seizure electrographic recordings of patients and use these connectivity matrices as the network structure in our model. The model simulates the dynamics of a bi-stable switch at every node in this network, meaning that every node starts in a background state, but has the ability to transit to a co-existing seizure state. Whether a transition happens in a node is partly determined by the stochastic nature of the input to the node, but also by the input the node receives from other connected nodes in the network. By conducting simulations with such a model, we can detect the average transition time for nodes in a given network, and therefore define nodes with a short transition time as highly epileptogenic. In a retrospective study, we found that in some patients the regions with high epileptogenicity in the model overlap with those identified clinically as the seizure onset zone. Moreover, it was found that the resection of these regions in the model reduces the overall likelihood of a seizure. Following removal of these regions in the model, we predicted surgical outcomes and compared these to actual patient outcomes. Our predictions were found to be 81.3% accurate on a dataset of 16 patients with intractable epilepsy. Intriguingly, in patients with unsuccessful outcomes, the proposed computational approach is able to suggest alternative resection sites. The model presented here gives mechanistic insight as to why surgery may be unsuccessful in some patients. This may aid clinicians in presurgical evaluation by providing a tool to explore various surgical options, offering complementary information to existing clinical techniques.