bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation of three-dimensional transient pollutant dispersion in low wind conditions using the 3D-GILTT technique
Authors: Da Silveira Viliam Cardoso , Buske Daniela , De Quadros Régis Sperotto
Published: August 2020

The aim of this work is to present a transient model in low wind conditionsto simulate the pollutants dispersion in the atmosphere. The dispersion model is based in the advection-diffusion equation and it considers the zonal and meridional components of the wind. The transient advection-diffusion equation is solved using integral transform techniques. In this work, the generalized integral transform and Laplace techniques are used, known in the literature as GILTT and which applied to the three-dimensional problem is called 3D-GILTT (Three-dimensional Generalized Integral Laplace Transform Technique). To validate the model, data from INEL experiment (Idaho National Engineering Laboratory) carried out in the USA were used. The model simulates the observed concentrations in a satisfactory way and can be used for regulatory air quality applications
Sensitivity analysis and optimization of a membrane reactor for hydrogen production through methane steam reforming
Authors: Caxiano Igor Nardi , Santos Lizandro de Sousa , Prata Diego Martinez
Published: August 2020

Hydrogen is one of most studied sources for clean power generation in the near future. Nowadays, hydrogen is mainly produced through methane steam reforming in packed bed reactors, with a promising alternative to this technology being the implementation of hydrogen-selective membrane reactors. This work compares the isothermal mathematical models of both designs by assessing the effects of multiple design variables on methane conversion, while also providing recommended operating conditions for maximum efficiency of the membrane reactor over the packed bed technology. Additionally, an optimization study is carried by dividing the reactor length in isothermal segments to achieve higher efficiency. Results showed that the membrane technology considerably increases hydrogen production, with temperature being the most influential variable on methane conversion. While the temperature profile optimization provided similar conversions compared to the isothermal models, the membrane reactor’s efficiency was increased, further justifying its implementation.
Types of flow in Green-Naghdi Thermoelasticity Theory
Authors: Garbugio Gilmar , Leite Henrique de Almeida Silva Mascalhusk Bernardo
Published: August 2020

In this paper we will show a review of the Green-Naghdi thermoelasticity theory.Such model have beautiful foundations which contains since the law of heat conduction proposed byFourier, fundamentals variables such as Helmholtz free energy, entropy, flux of heat and etc. and the constitutive hypothesis. The nature of partial differential equation of parabolic (PDE) type derived from classical thermoelasticity lead us to a mathematical inconsistency well-know as thermal signal speed paradox. We will show how Green-Naghdi model solved those mathematical inconsistency introducing different types of flow and giving us a hyperbolic PDE.
MHOLline 2.0: Workflow for automatic large-scale modeling and analysis of proteins
Authors: Rossi Artur Duque , Oliveira Pedro Henrique Eveling , Siqueira Dimitri Guglinski , Reis Victor Crisóstomo Cruz , Dardenne Laurent Emmanuel , Goliatt Priscila Vanessa Zabala Capriles
Published: August 2020

Genomes and their proteins can be analyzed by different perspectives, with different goals and applicability of results in several areas of research. In bioinformatics and computational biology, it is common the use of multiple combinations of programs and databases to extract information from the raw data. Choosing the proper program, setting its parameters, filtering the input files, extracting information from output files, and creating scripts for automating tasks can be challenging. This work describes the MHOLline, an online scientific workflow that provides a set of modules that enables a broad large-scale analysis of proteins (e.g. whole genomes) in a few hours. The version 1.0 (released in 2010), was wholly reformulated, and the new version 2.0 is available at www.mholline2.lncc.br. This version presents new features, modules, interface, code optimization, runtime reduction, more security, a new results visualization interface, and an automatic and user-friendly refinement page
An OpenMP implementation of the MuMM solver for porous media flow problems
Authors: Silva Sérgio Felipe Ferreira , Arimatéia Hanna Thaina Prates , Francisco Alexandre Santos , Assis Weslley Luiz da Silva
Published: August 2020

Multiscale methods are usually developed for solving second-order elliptic problems in which coef?cients are of multiscale heterogeneous nature. The Multiscale Mixed Method (MuMM) was introduced aiming at the ef?cient and accurate approximation of large ?ow problems in highly heterogeneous porous media. In the MuMM numerical solver, ?rst mixed multiscale basis functions are constructed, and next global domain decomposition iterations are performed to compute the discrete solution of the problems. However, this iterative procedure is a time-consuming step. In this paper, the authors improve the MuMM solver through the implementation of parallel computations in the step concerning the global iterative procedure. The parallel version of the solver employs the application programming interface Open Multi-Processing (OpenMP). The implementation with the OpenMP reduces signi?cantly the computational effort to perform the domain decomposition iterations, as indicated by the numerical results.
Multibody Simulation for Gravity-Driven Falling Film Using Computational Fluid Dynamics
Authors: Iglesias Susana Marrero , Dominguez Dany Sanchez , Mazaira Leorlen Yunier Rojas , Escrivá Alberto , Muñoz-Cobo José Luis , Rivera Yago , Berna Cesar
Published: August 2020

The annular flow two-phase regime appears in nuclear power plants cooling by water. On accidents with lost of cooling this regime determine the heat extraction conditions from the core.  The experimental facility Gerador de Película Ondulatoria (GEPELON) was constructed at Universitat Politècnica de València to study this phenomenon.  In this work, we use computational fluid dynamics techniques to simulate an air-water regime, specifically a gravity-driven falling liquid film in the GEPELON experimental facility. We consider a multibody geometry where the porous sintered of the input device is simulated in a realistic way. The Volume of Fluid (VOF) model was used in the resolution of the constitutive equations. We propose three geometric approximations to estimate film thickness, and simulation results were compared with experimental values. The simulation results show a good agreement with experimental measurements. Besides, no significant differences were observed between geometrical approximations for film thickness calculations.
A first study on earth-air heat exchanger in Pelotas
Authors: Nóbrega Eduardo de Sá Bueno , Brum Ruth da Silva , Ramalho Jairo Valões de Alencar , Quadros Régis Sperotto
Published: August 2020

Earth-air heat exchangers (EAHE) represent a promising option to reduce theheating/cooling load of buildings. Unlike traditional air conditioning systems, the EAHE employ a renewable source of energy and they can work using low electric power. Basically, EAHE employ underground ducts where the air is blown to exchange heat with the ground. Since the superficial layers of the Earth are warmer than outside air in winter and cooler than it in summer, the soil canbe used as a heat source or sink. Therefore, the air leaves the ducts at milder temperatures. Recent research has shown that the Brazilian south region, where prevails a subtropical climate, has a high potential for the use of EAHE. However, such references are still very limited. Hence, this work aims to analyze the thermal performance of EAHE considering the city of Pelotas, located in the south Brazilian state of Rio Grande do Sul. As a case study, we used in situ data, covering thesoil geotechnical profiles from a site in the city, which were obtained by a standard penetration test (SPT). To make the computer simulations, we used an analytical model, which was previously tested and validated. The results point out good prospects for the installation of these devices in the city of Pelotas, taking advantage of its geological potential
ON SPIN HAMILTONIAN FITS TO MÖSSBAUER SPECTRA OF NiFe2O4 NANOPARTICLES SYNTHESIZED BY CO-PRECIPITATION
Authors: Dias Filho Jose Higino , Aguilar Jorge Luis López , De Albuquerque Adriana Silva , Maia Renato Dourado , Barbosa Wesley de Oliveira , Ferreira Ernando Campos , Pereira Fellipe Silva , Benfica Kátia Ferreira Guimarães
Published: August 2020

Nanocrystalline NiFe2O4 particles prepared by chemical co-precipitation method were studied using magnetic measurements, 57Fe Mössbauer spectroscopy, X-ray diffraction, and transmission electron microscopy. Fits to Mössbauer spectra, in the range of 4.2 K – 300 K, were done using spin hamiltonians to describe both the electronic and nuclear interactions, a model of superparamagnetic relaxation of two levels (spin ½) and stochastic theory, a log-normal particle size distribution function as well as a dependency of the magnetic transition temperature and the anisotropy constant on particle diameter. We have used evolutionary strategies to fit the more complex Mössbauer spectra line shapes. The nanoparticles have an average size of 7 nm and exhibit superparamagnetism at room temperature. The saturation magnetization (Ms) at 4.2 K was determined from M vs. 1/H plots by extrapolating the value of magnetizations to infinite fields, to 24.21 emu/g and coercivity to 3.15 kOe. A magnetic anisotropy energy constant (K) 1.9´105 J/m3, at 4.2 K, were calculated from magnetization measurements. The synthesis, characterization, and functionalization of magnetic nanoparticles is a highly active area of current research located at the interface between materials science, biotechnology, and medicine. Superparamagnetic iron oxides nanoparticles have unique physical properties and have emerged as a new class of diagnostic probes for multimodal tracking and as contrast agents for magnetic resonance imaging (MRI).
PARAMETERIZATION OF MAGNETIC NANOPARTICLES MATHEMATICAL MODEL USING EVOLUTIONARY ALGORITHMS
Authors: Barbosa Wesley de Oliveira , Maia Renato Dourado , Dias Filho Jose Higino
Published: August 2020

In this paper, the evolutionary algorithms approach is applied to the parameterization of a mathematical model describing the Mössbauer spectra of nanogranular (or nanoparticle) magnetic systems. These systems exhibit physical properties very different from bulk specimens being of great interest for material science and its use as biosensors, magneto sensors, data storage, and magnetic fluids. The purpose of this work is to compare the performance between the Differential Evolution and the Evolutionary Strategies algorithms to optimize the model parameters which best fit the experimental Mössbauer spectra of nanoscale magnetic particles. Spectra of two samples (??iron foil and NiFe2O4 nanoparticles) were recorded, at room temperature, by a conventional Mössbauer spectrometer using a scintillation detector in transmission geometry with a 57Co/Rh source. Fits to Mössbauer spectra were done using spin hamiltonians to describe both the electronic and nuclear interactions; a model of superparamagnetic relaxation of two levels (spin ½) and stochastic theory; a lognormal particle size distribution function as well as a dependency of the magnetic transition temperature and the anisotropy constant on particle diameter. The evolutionary algorithms have been implemented using Python programming language. For comparison, the two algorithms obey the termination criterion of 6,000 evaluations of the objective function. The results presented show the efficiency of these algorithms in the optimization of the parameters and on the fits of the spectra.
MULTIOBJECTIVE PIG IRON COST OPTIMIZATION USING SIMPLEX PROJECTION
Authors: Guimarães Pedro Gabriel da Silva , Borges Carlos Cristiano Hasenclever , Arbex Wagner Antonio
Published: August 2020

This work presents a multiobjective optimization model to support the assembly of the raw materials budget for blast furnaces consumption in the production of pig iron, the main material for steelmaking. Given a set of materials and fabrication constraints, such as materials availability, their chemical compositions, the required features for the final product, etc, the objective of the model is to determine the amount of each material that generates the lowest cost solution with minimum wasteful. Due to conflicting objectives, defined by fabrication cost and slag rate, and based on characteristics of decision variables that formulate the problem, some of them in percentage form, an evolutionary multi-objective model has been developed associated with a projection onto a simplex technique aiming to improve the encoding of the genetic solutions. This projection is used in the genetic algorithm-based evolutionary model, wherein each new generated individual, their genes with percentage values are projected onto a simplex, a Euclidean space where the sum of all variables is the unit. The projection allows an intrinsic strategy to deal with percentage constraint of the model variables, increasing significantly the number of feasible individuals generated by the evolutionary procedure. The model has shown to be very effective and useful in determining several scenarios to support decisions making for the raw materials budget.
BRAIN THERMAL AND ELECTRICAL PROPERTIES ESTIMATION USING EXPERIMENTAL DATA FROM DEEP BRAIN STIMULATION LEAD
Authors: Jardim Lucas Correia da Silva , Abreu Luiz Alberto da Silva , Knupp Diego Campos , Silva Neto Antônio José da
Published: August 2020

Deep Brain Stimulation (DBS) is a well-established neurosurgery that alleviates the symptoms of several movement disorders and other brain related conditions. It works by placing a small lead containing electrodes inside the patient's brain and using them to electrically stimulate that area. Although this procedure is very common, little is known about its physiological effects on the brain and, on top of that, injuries caused from burning have been reported. The present work intends to formulate and solve a bioheat transfer model of the brain containing a DBS lead and, furthermore, to use this solution for solving an inverse problem of determining the thermal and electrical conductivities of the brain tissue using measurements supposedly obtained with a sensor inside the DBS lead.The results revealed that it is possible to estimate the both parameters especially when the measurements uncertainties are relatively small.
SIMULATION OF PULSATILE FLOW THROUGH ARTERIAL TREE MODELS
Authors: Santos Igor Pires dos , Reis Ruy Freitas , Queiroz Rafael Alves Bonfim de
Published: August 2020

In this work, an analytical scheme for evaluating the local wave characteristics of flow and pressure in 1D arterial tree’s models is implemented. An interactive computational environment was developed to simulate this scheme. The presented environment contains a compact class structure to enable the iteration and visualization of multiple objects. The results obtained are consistent with those from literature. The software developed provides the visualization of a blood flow simulation through a simple user interface.
PREDICTION OF THE PERFORMANCE OF BITUMINOUS MIXES USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEMS
Authors: Andrade Jonata Jefferson , Da Fonseca Leonardo Goliatt , Farage Michèle , Marques Geraldo Luciano de Oliveira
Published: August 2020

Accurately forecast performance and durability is a critical issue for improving the design of new and existing pavements. The poor pavement performance increases traffic congestion, compromises safety, and raises maintenance costs due to frequent repairs. The resilient modulus is one of the most critical unbound material property inputs in several current pavement design procedures. Recent studies have addressed the problem of resilient modulus prediction using different methods, including computational intelligence approaches. In this paper, a hybrid intelligent system called ANFIS (Adaptive Neuro-Fuzzy Inference System) is used for predicting the resilient modulus from an experimental database of 270 distinct compositions. ANFIS achieved superior performance when estimating the resilient modulus of bituminous mixes, which can potentially save laboratory resources.
A BAYESIAN APPROACH FOR THE SOLUTION OF INVERSE PROBLEMS TO ESTIMATE RADIATIVE PROPERTIES
Authors: Da Silva Cairo Martins , Guedes Gustavo Antunes , Abreu Luiz Alberto da Silva , Knupp Diego Campos , Da Silva Neto Antônio José
Published: August 2020

The main objective of the present work is related to the formulation and solutionof inverse problems in radiative heat transfer phenomena. The analysis consists in estimating parameters and functions of a participanting medium, such as optical thickness, single scattering albedo, diffusive reflectivities and phase function coefficients. It is performed with the numerical application of a Bayesian framework, which includes “Maximum a Posteriori” (MAP) and "Markov Chains Monte Carlo"(MCMC), within the Metropolis-Hastings procedure. These methodologiesproved to be effective for solving such problems.
Artificial neural network modeling approach for the prediction of five-day biological oxygen demand and wastewater treatment plant performance
Authors: Alsulaili Abdalrahman , Refaie Abdelrahman
Published: August 2020

The measurement of the wastewater BOD5 level requires five days, and the use of a prediction model to estimate BOD­5 saves time and enables the adoption of an online control system. This study investigates the application of artificial neural networks (ANNs) in predicting the influent BOD5 concentration and the performance of WWTPs. The WWTP performance was defined in terms of the COD, BOD, and TSS concentrations in the effluent. Sensitivity analysis was performed to identify the best-performing ANN network structure and configuration. The results showed that the ANN model developed to predict the BOD concentration performed the best among the three outputs. The top-performing ANN models yielded R2 values of 0.752, 0.612, and 0.631 for the prediction of the BOD, COD, and TSS concentrations, respectively. The optimal performing models were obtained (three inputs – one output), which indicated that the influent temperature and conductivity greatly affect the WWTP performance as inputs in all models. The developed prediction model for the influent BOD5 concentration attained a high accuracy, i.e., R2 = 0.754, which implies that the model is viable as a soft sensor for online control and management systems for WWTPs. Overall, the ANN model provides a simple approach for the prediction of the complex processes of WWTPs.
Dynamics of the behaviour of a vertical wetland (French system) operating in warm-climate conditions, evaluated by means of variables continuously measured in situ
Authors: de Andrade Moraes Mirene A. , Zumalacarregui Jorge A. García , Trein Camila Maria , von Sperling Marcos
Published: August 2020

The sewage treatment system in this study was operated with only the first stage of a French system of vertical wetlands, composed of two units in parallel and running with an extended feeding cycle (7 days). This research sought to evaluate and relate continuous variables measured in situ (dissolved oxygen (DO), pH and redox potential) throughout the feeding cycle, with measurements at distinct heights along the filter vertical profile. Additionally, the influence of the surface organic sludge deposit was investigated. A close link between the hydraulic behaviour and the effluent quality was verified, with both being related to the batch volume and the instantaneous hydraulic loading rate. The drop in DO as the feed days progressed could be related to the loss of hydraulic conductivity. A thicker sludge layer decreased the aeration capacity of the filter. The effluent was observed to be aerated when percolating through the medium. DO and pH data suggested that nitrification varied along the filter depth, the batch duration and the feed cycle. The monitored parameters may be indicative of the behaviour of other parameters.
The dynamics of a small social group: sociometric analysis development of a temporary children’s team
Authors: Maltseva Anna V. , Grudkovskaia Marina-Victoriia D.
Published: August 2020

The article is devoted to a sociometric study of the stages of development of a temporary children’s collective. A comparison of their features in the modern children’s health camp and the Soviet pioneer camp is made. The analysis of stages of development among modern teenagers is based on empirical data collected by Marina-Victoria Grudkovskaya at the children’s health camp in the Leningrad region during the winter shift from 28 December 2018 to 10 January 2019. Data on the processes of collective development in the pioneer camp were obtained from the works of Soviet researchers. The purpose of the study: to determine the independent constants of the stages of social dynamics of temporary children’s groups and their variables determined by the historical period of development of society. In this study, a temporary children’s team is understood as a small social group of adolescent children formed by age and existing during the next shift of 12 to 14 days. The theoretical and methodological basis of the work was structuralism and the theory of sociometry by Jacob Moreno. The empirical object of research: adolescent groups of children, the age of teenagers 14-16 years. Method: the sociometric experiment. Data processing and visualization was performed in the SociometryPro environment. The scientific novelty consists in obtaining new relevant data on the social dynamics of temporary groups of modern teenagers. The development of a temporary children’s collective is also considered taking into account the socio-historical period that determines the socio-cultural and socio-economic conditions of personal development of adolescents. Conclusions are made about the features of functioning, the process of acceptance and evaluation of social roles and behavior. In particular, it is established that the temporary children’s collective goes through constant stages that are repeated in all generations of children, regardless of the historical period of development of society and changing socio-economic and socio-cultural conditions of growing up of new generations. According to the authors, in the future, in the process of studying the social dynamics of a temporary children’s collective, it is advisable to develop names and characteristics of stages of its development that are relevant for modern children, children’s subculture and the sociology of childhood.
Systematic Review of Glucagon-Like Peptide One Receptor Agonist Liraglutide of Subjects with Heart Failure with Reduced Left Ventricular Ejection Fraction
Authors: Hamad Farah , Elnour Asim Ahmed , Elamin Abdelgadir , Mohamed Sasha , Yousif Isra , Don Judit , Abdi Semira , Al Amoodi Abdulla , Fathelrahman Ahmed Ibrahim , Gnana Kishore , Alanzi Fahad , Abubakar Abubakar B , Magboul Salma Mohammed , Ahmed Sahar Asim , Sadeq Adel
Published: August 2020

Background::

The major cardiovascular outcome trials on glucagon-like peptide one-receptor
agonists have examined its effect on hospitalization of subjects with heart failure; however,
very limited trials have been conducted on subjects with reduced left ventricular ejection fraction (r-
LVEF) as a primary outcome.

Objective::

We have conducted a systematic review of two major (FIGHT and LIVE) placebo-controlled
trials of liraglutide and its clinical effect on the ejection fraction of subjects with heart failure.

Methods::

Medline data was retrieved for trials involving liraglutide from 2012 to 2020. The inclusion
criteria for trials were: subjects with or without type 2 diabetes mellitus (T2DM), subjects
with heart failure with rLVEF, major trials (phase II or III) on liraglutide, trials included liraglutide
with defined efficacy primary outcome of patients with heart failure with rLVEF. The search was
limited to the English language, whereby two trials [FIGHT and LIVE] had been included and
two trials were excluded due to different primary outcomes. Participants (541) had been randomized
for either liraglutide or placebo for 24 weeks.

Results::

In the FIGHT trial the primary intention-to-treat, sensitivity, and diabetes subgroup analyses
have shown no significant between-group difference in the global rank scores (mean rank of
146 in the liraglutide group versus 156 in the placebo group; Wilcoxon rank-sum P=.31), number
of deaths, re-hospitalizations for heart failure, or the composite of death or change in NT-pro BNP
level (P= .94). In the LIVE trial, the change in the left ventricular ejection fraction (LVEF) from
baseline to week 24 was not significantly different between treatment groups. The overall discontinuation
rate of liraglutide was high in the FIGHT trial (29%, 86) as compared to that in the LIVE
trial (11.6%, 28).

Conclusion::

FIGHT and LIVE trials have demonstrated that liraglutide use in subjects with heart
failure and rLVEF was implicated with an increased adverse risk of heart failure-related outcomes.
The Relationship Between Depression and Menopause Symptoms: The PATH Model
Authors: Jenabi Ensiyeh , Fereidooni Bita , Khazaei Salman , Hamzehei Ronak , Tapak Leili
Published: August 2020

Background:

To date, no study has been performed on the relationship between depression
and perimenopausal symptoms using the Path model in Iran.

Objective:

This study aims to assess the relationship between depression and menopause symptoms
using the PATH model.

Methods:

A cross-sectional study was conducted for 4 months, in 2019, and 332 menopausal
women were enrolled in 14 public health centers. Data collection instruments included questionnaires
of demographic characteristics, anxiety instrument, Menopause Rating Scale, and the Beck
Depression short Inventory (BDI-S). The hypothesized mediators were assessed using Structural
Equation Modeling (SEM). The model included depression symptoms (dependent variable), anxiety
(mediators), number of alive children (moderator), and menopausal symptoms (independent variable).
Analyses were conducted by SPSS 16 and AMOS 20.

Results:

There was a significant positive correlation between menopause symptoms with total anxiety
(Rs=0.52), state anxiety (Rs=0.47), trait anxiety (Rs=0.46), and depression (Rs=0.54). Depression
had a significant positive correlation with total anxiety (Rs=0.64), trait anxiety (Rs=0.58), and state
anxiety (Rs=0.59). Also, the total mediating effect of total anxiety and depression and the total
moderating effect of the number of alive children were significant on menopause symptoms.

Conclusion:

According to the results of the present study, there is an association between depression
and menopausal symptoms. Therefore, health providers should pay more attention to the psychological
health of women during the perimenopausal period. The predictor factors should be considered
in both intervention and clinical assessment of menopause women.
Development of an Electrochemical DNA Biosensor Based on Gold Nanoparticles and Thiol Graphene Nanocomposite for Detection of a Specific nuc Gene from Staphylococcus aureus
Authors: Yan Lijun , Shao Bo , Zhang Xiaoping , Niu Yanyan , Dang Wendi , Cheng Hui , Li Guangjiu , Sun Wei
Published: August 2020

Background::

An electrochemical DNA biosensor based on gold nanoparticles (AuNPs)
and thiol graphene (TGR) nanocomposite modified carbon ionic liquid electrode (CILE) was developed
to detect a specific nuc gene of Staphylococcus aureus, which was further used in the analysis
of PCR amplification samples from unfrozen pork.

Objective::

The development of a DNA biosensor derived from AuNPs-coated TGR could be used
as a novel sensing method for the detection of specific ssDNA sequences in biological and clinical
samples.

Methods:

The electrochemical properties of modified CILE electrodes were determined by cyclic
voltammetry and electrochemical impedance spectroscopy, and the electrochemical performances
of the biosensor were investigated by differential pulse voltammetry.

Results::

This gene sensor was able to detect the specific nuc gene from Staphylococcus aureus
over the concentration range from 1.0×10-15 mol L-1 to 1.0×10-6 mol L-1 with a limit of detection of
4.5×10-16 mol L-1 (3σ), and it was applied in the detection of Staphylococcus aureus in an unfrozen
pork sample after PCR amplification of the nuc gene with satisfactory results.

Conclusion::

This gene biosensor showed high sensitivity and good selectivity, wide detection
range and low detection limit, which demonstrated an effective tool to detect specific nuc gene
sequences of Staphylococcus aureus.
Method Development and Validation for the Determination of Residual Solvents in Racecadotril by Gas Chromatography
Authors: Sattineni Sirisha Reddy , Joseph Alex , Das Subham , Chaitainya Balusu , Rao Subba
Published: August 2020

Background:

The presence of residual solvents in pharmaceuticals can be a potential
risk factor to human health because of its toxicity. Gas chromatography is used for its excellent separation
abilities and lower limit of detection. Racecadotril, an antidiarrheal drug, is reported having
four residual solvents, namely n-Hexane, isopropyl alcohol, toluene, and dimethylformamide.
Estimation of the amount of these solvents in active pharmaceutical ingredients to ensure that they
are within the permissible limits as per ICH guidelines is necessary.

Objective:

To develop and validate a new, simple, and sensitive gas chromatographic method for simultaneous
determination of n-Hexane, isopropyl alcohol, toluene, and dimethylformamide in racecadotril.

Methods:

The residual solvents of racecadotril were estimated using a gas chromatographic
method by direct injection using FID as a detector. This method employed a 30-meter long DB-FFAP
nitroterephthalic-acid-modified polyethene glycol column with 0.53 mm in inner diameter
and 1 μm film thickness. The separation was achieved using nitrogen as the carrier gas at a flow
rate of 2.8 mL/min using a split ratio of 1:10.

Results:

The peak shape for all the residual solvents from racecadotril was symmetric with excellent
resolution eluting at reasonable retention time. The limit of detection of n-Hexane, isopropyl alcohol,
Toluene, and dimethylformamide was found to be 6, 27, 14, and 42 ppm, respectively. The
developed method exhibited excellent linearity for each residual solvents in the range studied.

Conclusion:

The developed gas chromatographic method is simple, specific, precise, accurate, and
sensitive. Hence, the method can be successfully used in in the pharmaceutical companies and research
laboratories for simultaneous determination of residual solvents in racecadotril active pharmaceutical
ingredients.
Incentives for Multimodal Treatment-first Step Towards Pay for Quality (P4Q) for Chronic Care: Health Services Research from Germany
Authors: Romeyke Tobias , Noehammer Elisabeth , Stummer Harald
Published: August 2020

Background:

Pay for Quality (P4Q) is being discussed as an incentive to ensure high quality standards despite cost pressure in healthcare. However, P4Q can also have adverse effects, and the evidence for its effectiveness is limited, especially regarding chronic conditions and multimorbidity. For the treatment of the latter, specific evaluation criteria were defined. Whether these are feasible in the context of costs and remunerations is analyzed in this study using the German DRG system as an example. The aim is to show conditions under which P4Q can be effective.

Methods and Results:

Costs and remuneration for hospitals were compared for an exemplary geriatric indication, with and without complex treatment. Doing so, cost weights were shown to be more than triple for the latter. The results are applicable to health care systems with P4Q or similar approaches.

Conclusion:

Introducing complex treatments poses higher and costly demands regarding structure, processes, and interdisciplinary cooperation in organizations. Additional average costs can be calculated by comparison to regular treatment. Covering the extra costs creates the necessary conditions for P4Q and makes the implementation of complex treatments more likely. As high standards have to be guaranteed for complex treatments and patient satisfaction rises when these are introduced, quality improvements can be assumed. This study can inform Health policy (incentive models) medical societies, give impulses for quality management, and healthcare research (patient-oriented health, e.g. consumer-driven health care, shared decision-making). Future studies should report patient-related outcomes and investigate further diagnoses.
Effect of Fe Substitution on Dielectric, Electrical and Photocatalytic Behavior of ZnO Nanoparticles
Authors: Gawas Umesh B. , Pednekar Rajesh M. , Kothawale Manoj M. , Prasad Nand K. , Alla Santosh K.
Published: August 2020

Aims:

To develop a simple and cost effective synthetic strategy for the preparation of Fe
substituted ZnO nanoparticles.

Background:

The optoelectronic, electrical, dielectric, optical and magnetic properties of nanocrystalline
transition metal substituted ZnO are being explored worldwide for a variety of applications in
optoelectronic devices, solar cells, transparent thin film transistors, ultraviolet photodetector, piezoelectric
devices, light emitting diodes as well as in the biomedical field. Fe substituted ZnO nanoparticles
are being looked upon as promising material in dilute magnetic semiconductor system.

Objective:

To establish chemical identity and purity in order to ensure the complete substitution of
Fe3+ in ZnO lattice and study the effect of Fe substitution on dielectric, electrical and photocatalytic
behavior of ZnO nanoparticles.

Methods:

The nearly spherical ZnO and Fe substituted ZnO nanoparticles were synthesized at a low
temperature via solution combustion synthesis employing metal nitrate and sucrose.

Results:

The powder X-ray diffraction measurement has revealed the monophasic character and complete
substitution of Fe in the wurtzitic ZnO lattice. The lattice constants and aspect ratio of Fe substituted
ZnO were nearly constant and comparable to that of pristine ZnO. The average crystallite
size was found to decrease with increasing Fe substitution. SEM images revealed porous spongy
network like morphology. TEM measurements revealed a nearly spherical particle with narrow size
distribution between 10 nm - 25 nm.

Conclusion:

The dielectric constant and dielectric loss decrease upto x = 0.04 and increases with further
increase in Fe concentration. The lower value of dielectric loss in the higher frequency region
indicates the less lossy nature of Fe substituted samples. AC conductivity behaviour suggests small
polaron hopping type of conduction mechanism. The RT DC resistivity was found to decrease with
increasing Fe substitution. Pristine ZnO displayed very high degradation efficiency for photodegradation
of MB dye. The photodegradation efficiency was found to decrease considerably with increasing
Fe substitution.
Measuring Asymptomatic Growth of COVID-19; A Powerful Mechanism for Controlling the Disease Spread
Authors: Lau Keith
Published: August 2020

Background::

Coronavirus, called as, “the worst public health crisis for a generation,” is a
malevolent silent killer.

Objective::

One of the main concerns is containing the disease and avoiding the second wave of the pandemic,
likely to arise because of the symptomatic patients, while ensuring the safe execution of day to
day tasks.

Methods:

The indirect transmission of coronavirus from asymptomatic individuals during incubation
time and the identification of the people who have accidentally and unknowingly come in contact with
infected but asymptomatic patients pose a significant challenge to the health care providers.

Result::

Herein, for the first time, we have introduced a quantitative index; asymptomatic growth, to
indicate whether the COVID-19 community spread is under control and if economic activities can be
resumed.

Conclusion::

More importantly, our system provides a feasible mechanism for improving the index to a
level <1, a safety level at which normal economic activities can be conducted.
Qualidade de vida em diabéticos assistidos em Estratégia de Saúde da Família na região metropolitana de Porto Alegre, RS, Brasil
Authors: Brum Ferraz Etiane , Cechetto Fátima Helena , Riegel Fernando
Published: August 2020

Objetivo: Avaliar a qualidade de vida (QV) de pacientes diabéticos utilizando o instrumento Medical Outcomes Study 36-item Short Form Health Survey (SF-36). Métodos: estudo quantitativo, transversal e descritivo, realizado com 98 pacientes diabéticos assistidos em uma Estratégia de Saúde da Família da região metropolitana de Porto Alegre, Brasil, por meio de questionário sociodemográfico e do SF-36.  Resultados: 59 (60,2%) eram do sexo feminino e a faixa etária entre 50 e 69 anos correspondia a 46,9% da amostra. O diabetes mellitus tipo 2 foi o mais prevalente (68,4%) e a maioria (80,6%) fazia uso exclusivo de hipoglicemiantes orais. As médias dos domínios do SF-36 variaram entre 42,6 ± 44,9(Limitação por Aspectos Físicos) e 70,0 ± 30,1 (Aspectos Sociais). Os diabéticos participantes de atividade educativa apresentaram melhores escores de QV no domínio Dor (61,2 ± 24,8 vs. 45,4 ± 26,2; p = 0,015).  Conclusão: os escores do SF-36 apresentaram-se medianos, sugerindo influência negativa do diabetes na qualidade de vida dos participantes. As atividades educativas em grupo mostraram-se associadas a pontuações médias mais elevados dos domínios do escore de QV.
Information Needs About Cancer Treatment, Fertility, and Pregnancy: Qualitative Descriptive Study of Reddit Threads
Authors: Garg Ria , Rebić Nevena , De Vera Mary A
Published: August 2020

Background

A reproductive health implication of the increasing incidence of cancer among women is the impact of cancer treatment on fertility.

Objective

As patients are increasingly using the internet, particularly online forums, to seek and share experiences, our objective was to understand information needs about cancer treatment, fertility, and pregnancy of women with cancer as well as their caregivers.

Methods

We searched threads (original posts and responses) on four subreddit sites of Reddit (“r/Cancer,” “r/TryingForABaby,” “r/BabyBumps,” and “r/Infertility”) over a 5‐year period between February 4th, 2014 and February 4th, 2019. Threads with original posts involving a lived experience or question regarding cancer treatment and female fertility and/or pregnancy or parenting/having children from the perspective of either patient or caregiver were included in our analysis. We analyzed threads using thematic analysis.

Results

From 963 Reddit threads identified, 69 were analyzed, including 56 with original posts by women with cancer and 13 with original posts by caregivers. From threads made by patients, we identified themes on becoming a part of an online community, impacts of cancer treatment and fertility concerns on self and social relationships, making family planning decisions, and experiences with medical team. We also identified a theme on the impact of cancer treatment and fertility concerns on caregivers.

Conclusions

Reddit provided a rich pool of data for analyzing the information needs of women facing cancer. Our findings demonstrate the far-reaching impacts of cancer treatment and fertility on physical, mental, and psychosocial health for both patients and their caregivers.
Evaluating the Relationship Between Fitbit Sleep Data and Self-Reported Mood, Sleep, and Environmental Contextual Factors in Healthy Adults: Pilot Observational Cohort Study
Authors: Thota Darshan
Published: August 2020

Background

Mental health disorders can disrupt a person’s sleep, resulting in lower quality of life. Early identification and referral to mental health services are critical for active duty service members returning from forward-deployed missions. Although technologies like wearable computing devices have the potential to help address this problem, research on the role of technologies like Fitbit in mental health services is in its infancy.

Objective

If Fitbit proves to be an appropriate clinical tool in a military setting, it could provide potential cost savings, improve clinician access to patient data, and create real-time treatment options for the greater active duty service member population. The purpose of this study was to determine if the Fitbit device can be used to identify indicators of mental health disorders by measuring the relationship between Fitbit sleep data, self-reported mood, and environmental contextual factors that may disrupt sleep.

Methods

This observational cohort study was conducted at the Madigan Army Medical Center. The study included 17 healthy adults who wore a Fitbit Flex for 2 weeks and completed a daily self-reported mood and sleep log. Daily Fitbit data were obtained for each participant. Contextual factors were collected with interim and postintervention surveys. This study had 3 specific aims: (1) Determine the correlation between daily Fitbit sleep data and daily self-reported sleep, (2) Determine the correlation between number of waking events and self-reported mood, and (3) Explore the qualitative relationships between Fitbit waking events and self-reported contextual factors for sleep.

Results

There was no significant difference in the scores for the pre-intevention Pittsburg Sleep Quality Index (PSQI; mean 5.88 points, SD 3.71 points) and postintervention PSQI (mean 5.33 points, SD 2.83 points). The Wilcoxon signed-ranks test showed that the difference between the pre-intervention PSQI and postintervention PSQI survey data was not statistically significant (Z=0.751, P=.05). The Spearman correlation between Fitbit sleep time and self-reported sleep time was moderate (r=0.643, P=.005). The Spearman correlation between number of waking events and self-reported mood was weak (r=0.354, P=.163). Top contextual factors disrupting sleep were “pain,” “noises,” and “worries.” A subanalysis of participants reporting “worries” found evidence of potential stress resilience and outliers in waking events.

Conclusions

Findings contribute valuable evidence on the strength of the Fitbit Flex device as a proxy that is consistent with self-reported sleep data. Mood data alone do not predict number of waking events. Mood and Fitbit data combined with further screening tools may be able to identify markers of underlying mental health disease.
Asynchronous mHealth Interventions in Rheumatoid Arthritis: Systematic Scoping Review
Authors: Seppen Bart F , den Boer Pim , Wiegel Jimmy , ter Wee Marieke M , van der Leeden Marike , de Vries Ralph , van der Esch Martin , Bos Wouter H
Published: August 2020

Background

Mobile devices such as smartphones and tablets have surged in popularity in recent years, generating numerous possibilities for their use in health care as mobile health (mHealth) tools. One advantage of mHealth is that it can be provided asynchronously, signifying that health care providers and patients are not communicating in real time. The integration of asynchronous mHealth into daily clinical practice might therefore help to make health care more efficient for patients with rheumatoid arthritis (RA). The benefits have been reviewed in various medical conditions, such as diabetes and asthma, with promising results. However, to date, it is unclear what evidence exists for the use of asynchronous mHealth in the field of RA.

Objective

The objective of this study was to map the different asynchronous mHealth interventions tested in clinical trials in patients with RA and to summarize the effects of the interventions.

Methods

A systematic search of Pubmed, Scopus, Cochrane, and PsycINFO was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Studies were initially screened and later assessed by two independent researchers. Disagreements on inclusion or exclusion of studies were resolved by discussion.

Results

The literature search yielded 1752 abstracts. After deduplication and screening, 10 controlled intervention studies were included. All studies were assessed to be at risk for bias in at least one domain of the Cochrane risk-of-bias tool. In the 10 selected studies, 4 different types of mHealth interventions were used: SMS reminders (to increase medication adherence or physical activity; n=3), web apps (for disease monitoring and/or to provide medical information; n=5), smartphone apps (for disease monitoring; n=1), and pedometers (to increase and track steps; n=1). Measured outcomes varied widely between studies; improvements were seen in terms of medication compliance (SMS reminders), reaching rapid remission (web app), various domains of physical activity (pedometer, SMS reminders, and web apps), patient-physician interaction (web apps), and self-efficacy (smartphone app).

Conclusions

SMS reminders, web apps, smartphone apps, and pedometers have been evaluated in intervention studies in patients with RA. These interventions have been used to monitor patients or to support them in their health behavior. The use of asynchronous mHealth led to desirable outcomes in nearly all studies. However, since all studies were at risk of bias and methods used were very heterogeneous, high-quality research is warranted to corroborate these promising results.