nils-herrmann/clean_scirepeval huggingface dataset:
Ni and Mn Promoted Mesoporous Co3O4: A Stable Bifunctional Catalyst with Surface Structure Dependent Activity for Oxygen Reduction Reaction and Oxygen Evolution Reaction.
Venue: ACS applied materials interfaces

Efficient bifunctional catalysts for electrochemical oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are highly desirable due to their wide applications in fuel cells and rechargeable metal air batteries. However, the development of nonprecious metal catalysts with comparable activities to noble metals is still challenging. Here we report a one step wet chemical synthesis of Ni /Mn promoted mesoporous cobalt oxides through an inverse micelle process. Various characterization techniques including powder X ray diffraction (PXRD) N2 sorption, transmission electron microscopy (TEM) and scanning electron microscopy (SEM) confirm the successful incorporation of Ni and Mn leading to the formation of Co Ni(Mn) O solid solutions with retained mesoporosity. Among these catalysts, cobalt oxide with 5% Ni doping demonstrates promising activities for both ORR and OER, with an overpotential of 399 mV for ORR (at 3 mA/cm(2) and 381 mV (at 10 mA/cm(2) for OER. Furthermore, it shows better durability than precious metals featuring little activity decay throughout 24 h continuous operation. Analyses of cyclic voltammetry (CV) X ray photoelectron spectroscopy (XPS) Raman, and O2 temperature programmed desorption (O2 TPD) reveal that redox activity of Co(3+ to Co(4+ is crucial for OER performance, while the population of surface oxygen vacancies and surface area determine ORR activities. The comprehensive investigation of the intrinsic active sites for ORR and OER by correlating different physicochemical properties to the electrochemical activities is believed to provide important insight toward the rational design of high performance electrocatalysts for ORR and OER reactions.
Impedimetric humidity sensor based on the use of SnO2 Co3O4 spheres
Venue: Journal of Materials Science: Materials in Electronics

The article describes synthesis and sensing properties of SnO2 Co3O4 spheres composed of aggregated nanoparticles. Co3O4 was doped with pristine SnO2, and the resulting nanocomposite spheres were incorporated into a silicon adhesive. This material is shown to enable impedimetric sensing of relative humidity (RH) The impedance of the material decreases by 80% at a 1.0 kHz working frequency and by a factor of 2500 at 100 Hz. Capacitance increases by 70% at 1.0 kHz frequency and by a factor of 1509 at 100 Hz. The sensor works in the 10 90% RH range at temperatures from 10 to 80 degC. SnO2 Co3O4 based humidity sensor exhibited high sensitivity which makes it suitable material for the utilization in humidity meter.
Extensible Real Time Software Design Inconsistency Checker A Model Driven Approach

Unidentified inconsistencies in software design models can obstruct the desired time to market attribute of software. The consequences of them are far reaching besides being reflected in the implementation. Detecting and tracking inconsistencies in model driven software development has been challenging. However, there is an encouraging fact that the emergence of Unified Modelling Language (UML) brought uniform notations to be used across the globe. Many UML based design consistency checkers came into existence. However an effective automated approach for consistency checking is still desired as it can lead to early detection of inconsistencies. Thus frequently occurring cost and budget overruns in software industry can be eliminated. Towards this end this paper implemented a framework named Extensible Real Time Software Design Inconsistency Checker (XRTSDIC) The framework enables software engineers to have real time feedback on model inconsistencies throw light into the issues early as it is wise to use a stitch in time and avoid eight. The consistency checker not only exploits consistency rules but also viewpoints besides supporting a degree of formal tolerance for inconsistencies. This makes the proposed system flexible with user description while resolving inconsistencies. Our empirical evaluation shows that implemented approach is comparable with previous approaches with significant improvement in speed, scalability and accuracy in detecting inconsistencies in software design models. The prototype demonstrates the proof of concept. Index Terms tracking inconsistencies, unified modelling language, software design models.
Universal Approximation Results for the Temporal Restricted Boltzmann Machine and the Recurrent Temporal Restricted Boltzmann Machine
Venue: J. Mach. Learn. Res.

The Restricted Boltzmann Machine (RBM) has proved to be a powerful tool in machine learning, both on its own and as the building block for Deep Belief Networks (multi layer generative graphical models) The RBM and Deep Belief Network have been shown to be universal approximators for probability distributions on binary vectors. In this paper we prove several similar universal approximation results for two variations of the Restricted Boltzmann Machine with time dependence, the Temporal Restricted Boltzmann Machine (TRBM) and the Recurrent Temporal Restricted Boltzmann Machine (RTRBM) We show that the TRBM is a universal approximator for Markov chains and generalize the theorem to sequences with longer time dependence. We then prove that the RTRBM is a universal approximator for stochastic processes with _nite time dependence. We conclude with a discussion on efficiency and how the constructions developed could explain some previous experimental results.
Speech Bandwidth Extension Using Recurrent Temporal Restricted Boltzmann Machines
Venue: IEEE Signal Processing Letters

In this paper, we present a new speech bandwidth extension method (BWE) using recurrent temporal restricted Boltzmann machine (RTRBM) The conventional Gaussian mixture model (GMM) based and deep neural networks (DNNs) based BWE methods perform stably and effectively. However, the mapping function of GMM based methods is a piecewise linear transformation, which is insufficient to model the complex nonlinear mapping relationship between the spectral envelope features of low frequency (LF) and high frequency (HF) In the conventional DNNs methods, temporal correlations across speech frames are ignored, resulting in spectral detail loss of the reconstructed speech by BWE. To counter these issues, a multilayer DNN which is composed of two RTRBMs and a feedforward neural network (NN) is employed to obtain time information and model deep nonlinear relationships between the spectral envelope features of LF and HF. The proposed method takes advantage of the strong ability of RTRBM in discovering the temporal correlation in the high order space and modeling deep nonlinear relationships between input and output. Both the objective and subjective evaluations indicate that our proposed method outperforms the conventional GMM based methods and other NN based methods.
Towards smart factory for industry 4.0: a self organized multi agent system with big data based feedback and coordination
Venue: Comput. Networks

The proliferation of cyber physical systems introduces the fourth stage of industrialization, commonly known as Industry 4.0. The vertical integration of various components inside a factory to implement a flexible and reconfigurable manufacturing system, i.e. smart factory, is one of the key features of Industry 4.0. In this paper, we present a smart factory framework that incorporates industrial network, cloud, and supervisory control terminals with smart shop floor objects such as machines, conveyers, and products. Then, we provide a classification of the smart objects into various types of agents and define a coordinator in the cloud. The autonomous decision and distributed cooperation between agents lead to high flexibility. Moreover, this kind of self organized system leverages the feedback and coordination by the central coordinator in order to achieve high efficiency. Thus, the smart factory is characterized by a self organized multi agent system assisted with big data based feedback and coordination. Based on this model, we propose an intelligent negotiation mechanism for agents to cooperate with each other. Furthermore, the study illustrates that complementary strategies can be designed to prevent deadlocks by improving the agents' decision making and the coordinator's behavior. The simulation results assess the effectiveness of the proposed negotiation mechanism and deadlock prevention strategies.
Revenue oriented bandwidth allocation in optical OFDM intra data center networks
Venue: 2016 IEEE International Conference on Communications (ICC)

Optical orthogonal frequency division multiplexing (O OFDM) technology, which divides fiber bandwidth into multiple OFDM subcarriers, enables high bandwidth and fine granularity intra data center networks (DCNs) to provide powerful platform for cloud computing. An important issue raised in such O OFDM based intra DCNs is how to assign contiguous subcarriers for connection requests with the aim to balance the revenue of cloud providers with the connection performance of tenants. In this paper, considering the limited bandwidth, we firstly propose a revenue model that introduces a penalty policy for assuring connection performance according to the reservation price paid by tenants. We then study revenue oriented bandwidth allocation problem over O OFDM intra DCNs based on the proposed revenue model. For a special case that there is no background traffic while conducting bandwidth allocation, we show that the problem can be transformed into a minimum cost network flow problem. For the case that extremely strict penalty is regulated, we design a two phase algorithm to solve the problem. An efficient heuristic algorithm is also proposed to settle the problem with general form. The efficiency of the work is finally demonstrated by simulations.
Orchid conservation: further links.
Venue: Annals of botany

Due in great part to their often complex interactions with mycorrhizal fungi, pollinators and host trees, Orchidaceae present particular challenges for conservation. Furthermore, orchids, as potentially the largest family of angiosperms with >26000 species, species complexes and frequent hybrid formation, are complex to catalogue. Following a highlight in 2015, a further seven papers focusing on orchids, their interactions with beneficial organisms, pollinators and mycorrhiza, and other factors relating to their conservation, including threats from human utilization and changing land use, are presented here.  The production of an online flora of all known plants and an assessment of the conservation status of all known plant species as far as possible, to guide conservation action are the first two targets of the Global Strategy for Plant Conservation Without knowing how many species there are and how they should be circumscribed, neither of these targets is achievable. Orchids are a fascinating subject for fundamental research with rapid species evolution, specific organ structure and development, but they also suffer from high levels of threat. Effective orchid conservation must take account of the beneficial interactions with fungi and pollinators and the potentially detrimental effects of over collection and changes in land use.
Initial Conditions and Efficient Estimation in Dynamic Panel Data Models: An Application to

This paper provides a methodology for efficient estimation of dynamic panel data models under different assumptions concerning initial condi tions and variance assumptions. In the analysis of panel data models that may involve lagged dependent variables, concerns about the initial conditions reflect the fact that most panel data sets have a relatively small time series dimension. Our model specification is a linear first order dynamic model in which there are assumed to exist an identifying subset of strictly exogenous regressors. Under all but the most trivial assumption concerning the initial conditions the standard GLS procedure is inconsistent. We argue that our approach provides a natural procedure for testing assumptions concerning the process underlying the initial conditions. The methodology is applied to the estimation of a dynamic model of investment beha viour using panel data.
Perioperative considerations in children with autism spectrum disorder
Venue: Current opinion in anaesthesiology

Children with autism often present a challenge to the anesthesiologist. This review summarizes the current experiences and recommendations for the perioperative management of this unique group of patients. Recent findings Autism is the fastest growing neurodevelopmental disorder in the world. Increased recognition and public awareness of the disease is driven largely by the advances in research. A large body of evidence exists that identifies the role of genetic, environmental, biological, and developmental factors in the origin of autism. The anesthesia literature consists mostly of case reports. Recent publications are reporting management strategies and evaluation of this patient population's perioperative experiences.  Patients with autism spectrum disorder are a heterogeneous group and often need general anesthesia for different procedures and studies. Familiarity with each patient's behavioral specifics and efforts to alleviate stress is of paramount importance for a smooth perioperative course with minimal adverse events.
Child marriage and maternal health risks among young mothers in Gombi, Adamawa State, Nigeria: implications for mortality, entitlements and freedoms.
Venue: African health sciences

Efforts toward liberation of the girl child from the shackles of early marriage have continued to be resisted through tradition, culture and religion in some parts of Nigeria.  This study therefore examines the maternal health implications of early marriage on young mothers in the study area.  Multistage sampling technique was employed to obtained data from 200 young mothers aged 15 24 years who married before aged 16 years.  The study reveals that more than 60% had only primary education while more than 70% had experienced complications before or after childbirth. Age at first marriage, current age, level of education and household decision making significantly influence (P<0.005) maternal health risks in the study area. The study establishes that respondents in age group 15 19 years are 1.234 times more likely to experience complications when compared with the reference category 20 24 years. Entitlements and freedom that are highly relevant to reduction of maternal mortality, provided by international treaties are inaccessible to young women in the study area.  Strategies to end child marriage in the study area should include mass and compulsory education of girls, provision of other options to early marriage and childbearing and involvement of fathers in preventing and ending the practice.
Teen Mothers' Experience of Intimate Partner Violence: A Metasynthesis
Venue: ANS. Advances in nursing science

Pregnant and parenting teens suffer higher rates of intimate partner violence (IPV) than older mothers. This qualitative metasynthesis explores teen mothers' experience with IPV during pregnancy and postpartum. Organized by the metaphor of a web, findings highlight how pervasive violence during childhood contributes to teen pregnancy and the risk of IPV as violence is normalized. The web constricts through the partner's control as violence emerges or worsens with pregnancy. Young mothers become increasingly isolated, and live with the physical and psychological consequences of IPV. Trauma informed nursing practice is needed to support teen mothers in violent intimate relationships to spin a new web.
Do Young Mothers and Fathers Differ in the Likelihood of Returning Home?
Venue: Journal of marriage and the family

Building on research examining "boomerang" adult children, I examine multigenerational living among young parents. Returning home likely differs between young mothers and fathers given variation in socioeconomic characteristics, health and risk taking, their own children's coresidence, and union stability. Using the National Longitudinal Survey of Youth 1997 (NLSY97) I find that more than 40% of young parents (N 2,721) live with their own parents at first birth or subsequently. Mothers are generally less likely to move home than fathers but only when not controlling for child coresidence and union stability. Individuals who live with all their children are less likely to return home, and controlling for child coresidence reverses gender differences, though this association disappears in the full model. Young parents who are stably single and those who experience dissolution are highly likely to return home compared to the stably partnered, with the association significantly stronger for fathers than mothers.
Learning executive function and early mathematics: Directions of causal relations

Although there has been much recent attention to young children's development of executive function and early mathematics, few studies have integrated the two. Here we review the evidence regarding executive function and mathematic achievement in the early years. After defining the executive function processes we consider, we briefly address the question of whether executive function can be taught in schools. We then turn to the relations between executive function and achievement. We begin with a review of the larger literature on correlations between the two, both concurrent and predictive. This leads to the fewer but more directly educationally relevant causal studies. We conclude that developing both executive function processes and mathematical proficiencies is essential for young children and suggest that high quality mathematics education may have the dual benefit of teaching this important content area and developing executive function processes.
The Functional Response of B Cells to Antigenic Stimulation: A Preliminary Report of Latent Tuberculosis
Venue: PloS one

Mycobacterium tuberculosis (M.tb) remains a successful pathogen, causing tuberculosis disease numbers to constantly increase. Although great progress has been made in delineating the disease, the host pathogen interaction is incompletely described. B cells have shown to function as both effectors and regulators of immunity via non humoral methods in both innate and adaptive immune settings. Here we assessed specific B cell functional interaction following stimulation with a broad range of antigens within the LTBI milieu. Our results indicate that B cells readily produce pro and anti inflammatory cytokines (including IL 1b, IL 10, IL 17, IL 21 and TNF a) in response to stimulation. TLR4 and TLR9 based stimulations achieved the greatest secreted cytokine production response and BCG stimulation displayed a clear preference for inducing IL 1b production. We also show that the cytokines produced by B cells are implicated strongly in cell mediated communication and that plasma (memory) B cells (CD19+CD27+CD138+ is the subset with the greatest contribution to cytokine production. Collectively our data provides insight into B cell responses, where they are implicated in and quantifies responses from specific B cell phenotypes. These findings warrant further functional B cell research with a focus on specific B cell phenotypes under conditions of active TB disease to further our knowledge about the contribution of various cell subsets which could have implications for future vaccine development or refined B cell orientated treatment in the health setting.
Opportunistic Function Computation for Wireless Sensor Networks
Venue: IEEE Transactions on Wireless Communications

Function computation over wireless sensor networks is investigated, where a set of K sensors observe their sensor readings and a fusion center wishes to learn a predefined function of the sensor readings via fading multiple access channels (MACs) In this paper, the arithmetic sum and type functions are considered since they can yield various fundamental sample statistics such as mean, variance, maximum, and minimum. We propose a novel opportunistic in network computation (INC) framework in which a subset of sensors with large channel gains opportunistically participate in the transmission at each time, while all sensors simultaneously send their observations or only a single sensor sends its observation in the conventional schemes. We mathematically analyze the long term average computation rate of the proposed INC, and prove that it achieves a nonvanishing computation rate even when the number of sensors K tends to infinity, which is in fact a significant improvement and the first theoretical result in fading MACs. Note that the computation rates of the conventional schemes become zero as K increases. We further show that a similar multiuser diversity gain is still achievable under delay constraints, which implies that the proposed INC is restricted to exploit a fixed and finite number of time slots (or fading instances) for the function computation.
La discalculia en el rendimiento academico en el area de matematica de los ninos de quinto grado de educacion general basica paralelo "c" de la unidad educativa "Chunchi" canton, Chunchi provincia Chimborazo periodo lectivo 2014 2015

Referring to the academic field for the improvement and quality of education is required to work with professional and updated mystique by each of the teachers, the educational needs of students lead to a radical change in the teaching learning in education centers. Considering all this background consideration gets a profound study whose primary objective is to determine the problems of dyscalculia, affecting significantly in academic performance in the area of mathematics of fifth graders of basic general education in the Educative Unit Chunchi, it is exposed to clearly and precisely point conceptualizations on the subject, making a crossing by different ideas of different authors and works that approach the subject from different positions, a listing considered for defining basic terms so that there is a better understanding the hypothesis arisen from the s research is exposed, taking into account the two variables of the same study that allowed us to operationalize. For this research were considered various methods such as the scientific, inductive, deductive, analytical and synthetic which have served as guide and orientation for the study. The research is exploratory, descriptive, explanatory and bibliographical type, the design is quasi experimental since children were observed when applying the brochure. The population is composed of 35 students. The techniques have been used as instruments of observation and the observation sheet is structured with 10 items, it has been managing a procedure for tabulating using tables and pies to perform the examination. Similarly conclusions are established based on the obtained results which takes into account the criteria issued by the investigating interpretations. Bibliographical sources and the respective annexes are presented where the proposal is submitted with the development of a guide of activities that encourage solving the problem under study.
Coexistence of Fetal Cardiac Malformation and Maternal Drug Induced Lupus: Is Lamotrigine Safe?
Venue: American journal of therapeutics

Lamotrigine (LTG) is a widely used second generation antiepileptic drug for long term therapy of epileptic patients. Although LTG monotherapy during pregnancy is assumed to be relatively safe, teratogenic effects related to LTG has been reported previously. The presence of fetal malformations and maternal drug induced lupus erythematosus concurrently in a pregnant women using LTG have not been reported before. We herein report a term infant with coarctation of aorta and ventricular septal defect, who was born to a mother treated with LTG for epilepsy before conception and throughout pregnancy. The mother was diagnosed with drug induced lupus erythematosus at the 36th gestational week, and the symptoms resolved after discontinuation of the drug. Fetal cardiac anomalies should be searched in mothers who were exposed to LTG during pregnancy.