bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intimate Partner Violence and Associated Factors among Married Women live in Hosanna Town, Southern Ethiopia
Authors: Temesgen Tigist , Teji Kedir , Dheresa Merga , Asegid Agezegn 
Published: September 2019

Abstract
ABSTRACT Background: Intimate partner violence is a problem of pandemic proportion affecting majority of world women the literature shows that pattern and underlying cause of women violence have socio-demographic and cultural difference is common in most parts of Ethiopia. To best of investigator knowledge no studies done on intimate partner violence on married women of reproductive age group in the study area. Therefore the aim of this study is to assess the intimate partner violence prevalence and its associated factors. Methods: A community based cross-sectional study design was used from March 1-15/2019 among 602 married women of Hosanna town Sothern Ethiopia. Systematic random sampling technique was used to select the study samples. Data were collected using pretested structured questionnaire, data entered into Epi-data version 3.1 software and exported to SPSS version 20 for analysis. Binary and multivariate logistic regressions were used to identify factors associated with intimate partner violence. Results: The prevalence of overall intimate partner violence among married women was 58.8 %( 54.8-62.4). Of which 45.3% reported psychological violence, while 38.1% of participant reported sexual violence. Partners who drink alcohol [(AOR= 1.44, 95%CI=1.133-2.09)], Partner’s smoke cigarettes [(AOR=4.16,CI=2.117-8.20)], partner’s experience of Fighting habit with other people [(AOR=1.56 CI=1.06-2.29),Has another wife[(AOR=1.60 CI=1.09- 2.36)],low wealth index household [(AOR= 2.97 CI=1.41-6.27)], and medium wealth index households [(AOR=2.636 CI=1.173-5.920)] were significantly associated with intimate partner violence. Conclusion: Study indicated that prevalence of intimate partner violence found to be high and affected by various factors. The problem sought harmonious urgent attention at all levels of societal hierarchy including policymakers, local leader, institutions and local community gathering and structures. Key words : Intimate partner violence, associated factors, women, Hossana, Ethiopia
Quality of life of people with schizophrenia compared to controls: A case-control study
Authors: Woldemariam Abraha Gosh , Kahsay Haftom Desta 
Published: September 2019

Abstract
Objective: purpose of this study was to compare the quality of life of people with schizophrenia to healthy controls.
Results: the present study demonstrated that respondents with schizophrenia have significantly lower scores in Physical component summary ( U=70.5, z=-8.695, p<..001, r=-.734 ), mental component summary ( U=79.0,z= -8.634 p<.001, r=-.730 ), Physical functioning ( U=310, z-9.553, p<.001, r=-.808 ), Role Physical ( U=419, z=-8.975, p<.001, r=-.759 ), Body pain ( U=1395.5, z=-3.501, p<.001, r=-.296 ), General health ( U=320,z=-7.514, p<.001, r=-.635 ), Vitality ( U=353, z=-7.398, p=.001, r=-.625 ), Social functioning ( U=213.5, z=-9.398, p<.001, r=-.794 ), Role emotion ( U=144.5, z=-985, p<.001, r=-.844 ) and Mental health ( U=178, z=-8.199, p<.001, r=-.693 ) compared with healthy controls.
Key words: Quality of life, Schizophrenia, Controls, Case-Control
CHARACTERIZATION OF THE SUM OF BINOMIAL RANDOM VARIABLES UNDER RANKED SET SAMPLING
Authors: Verma Vivek , Nath Dilip C. 
Published: September 2019

Abstract
In this paper, we examined the characteristics of the sum of independent and non-identical set of binomial ranked set samples, where each set has different order depending success probability. The characterization is done by establishing the general recurrence relations for two different situations based on the number of cycle, which is initially pre-assumed as a constant integer and when it is a random variable. To extend the knowledge about the characteristics of sum in terms of their behaviour and pattern, first four moments i.e., mean, variance, skewness and kurtosis are derive and compared with the sum of binomial simple random samples with same success probability. The proposed procedure has been illustrated through a real-life data on survivorship of children below one year in Empowered Action Groups (EAG) states of India.
OUTLIER DETECTION IN THE ANALYSIS OF NESTED GAGE R&R, RANDOM EFFECT MODEL
Authors: Abduljaleel Mohammed , Midi Habshah , Karimi Mostafa 
Published: September 2019

Abstract
Measurement system analysis is a comprehensive valuation of a measurement process and characteristically includes a specially designed experiment that strives to isolate the components of variation in that measurement process. Gage repeatability and reproducibility is the adequate technique to evaluate variations within the measurement system. Repeatability refers to the measurement variation obtained when one person repeatedly measures the same item with the same Gage, while reproducibility refers to the variation due to different operators using the same Gage. The two factors factorial design, either crossed or nested factor, is usually used for a Gage R&R study. In this study, the focus is only on the nested factor, random effect model. Presently, the classical method (the method of analysing data without taking into consideration the existence of outliers) is used to analyse the nested Gage R&R data. However, this method is easily affected by outliers and, consequently, the measurement system’s capability is also affected. Therefore, the aims of this study are to develop an identification method to detect outliers and to formulate a robust method of measurement analysis of nested Gage R&R, random effect model. The proposed methods of outlier detection are based on a robust mm location and scale estimators of the residuals. The results of the simulation study and real numerical example show that the proposed outlier identification method and the robust estimation method are the most successful methods for the detection of outliers.
ESTIMATION OF PRODUCT OF TWO POPULATION MEANS BY MULTI-AUXILIARY CHARACTERS UNDER DOUBLE SAMPLING THE NON-RESPONDENTS
Authors: Khare B. B. , Sinha R. R. 
Published: September 2019

Abstract
This paper considers the problem of estimating the product of two population means using the information on multi-auxiliary characters with double sampling the non-respondents. Classes of estimators are proposed for estimating P under two different situations [discussed by Rao (1986, 90)] using known population mean of multi-auxiliary characters. Further, this problem has been extended to the case when population means of the auxiliary characters are unknown and they are estimated on the basis of a larger first phase sample. In this situation, a class of two phase sampling estimators for estimating P is suggested using multi-auxiliary characters with unknown population means in the presence of non-response. The expressions of bias and mean square error of all the proposed estimators are derived and their properties are studied. An empirical study using real data sets is given to justify the theoretical considerations.
COMPARATIVE ANALYSIS OF POVERTY IN FAMILIES WITH A DISABLED CHILD AND FAMILIES WITH NON-DISABLED CHILDREN IN POLAND IN THE YEARS 2014 AND 2016
Authors: Komorowska Olga , Kozłowski Arkadiusz , Słaby Teresa 
Published: September 2019

AbstractThe presence of a child with disabilities in a family presents more challenging conditions than the presence of a non-disabled child. One of the difficulties is of financial nature. One of the parents often has to give up their job to care for the child, which shrinks the household income. At the same time, the family has higher expenses resulting from, e.g. costs of treatment. All this increases the risk of falling into poverty. The goal of this paper is to analyse the financial situation of households with a disabled child, mainly in the context of poverty, and compare it to the financial situation of households with non-disabled children. The study is based on data from Polish Household Budget Survey, covering two years, 2014 and 2016. The study revealed that families with a disabled child are generally poorer than families with non-disabled children. The financial situation improved over the studied period in both types of families, but the improvement in the families with a disabled child was much greater. The main factor in reducing the risk of poverty in both types of families is the education attainment level of the reference person (the household head), which should be at least upper secondary.
Bio-stimulation of anaerobic digestion by low intensity ultrasonication
Authors: Tyagi Vinay Kumar , Tien Aron Loh Shu , Ahmed Banafsha , Gautam Arti 
Published: September 2019

Abstract
Low intensity ultrasonication (US) was applied to stimulate the biological activities in anaerobic digestion (AD) process. The enhancement in methane production was used to investigate the sono-biostimulation effects on the process performance. The 32% higher CH4 production was observed over control at best US intensity and irradiation time of 0.0028 W/mL and 120 s, respectively. The sono-biostimulation effects in terms of higher CH4 generation over control lasted for 45 h. The increase in the concentration of NH4+-N and K+ considered the indication of cell lysis under applied US conditions. At best US intensity and irradiation time, the NH4+-N and K+ fraction in the medium remained similar as of control, which indicated that no cell lysis occurred. The preliminary findings of the study showed that low intensity US can be a promising solution to enhance the process efficiency in terms of higher methane production with minimal energy requirement.
Performance evaluation of the ISMLR package for predicting the next day's influent wastewater flowrate at Kirie WRP
Authors: Zhu Jun-Jie , Anderson Paul R. 
Published: September 2019

Abstract
Soft-sensor applications for wastewater management can provide valuable information for intelligent monitoring and process control above and beyond what is available from conventional hard sensors and laboratory measurements. To realize these benefits, it is important to know how to manage gaps in the data time series, which could result from the failure of hard sensors, errors in laboratory measurements, or low-frequency monitoring schedules. A robust soft-sensor system needs to include a plan to address missing data and efficiently select variable(s) to make the most use of the available information. In this study, we developed and applied an enhanced iterated stepwise multiple linear regression (ISMLR) method through a MATLAB-based package to predict the next day's influent flowrate at the Kirie water reclamation plant (WRP). The method increased the data retention from 77% to 93% and achieved an adjusted R2 up to 0.83 by integrating with a typical artificial neural network.
A pilot bioretention system with commercial activated carbon and river sediment-derived biochar for enhanced nutrient removal from stormwater
Authors: Sang Min , Huang Miansong , Zhang Wei , Che Wu , Sun Huichao 
Published: September 2019

Abstract
Bioretention is an effective technology for urban stormwater management, but the nutrient removal in conventional bioretention systems is highly variable. Thus, a pilot bioretention column experiment was performed to evaluate the nutrient control of systems with commercial activated carbon and river sediment-derived biochar. Significant chemical oxygen demand (COD) and total phosphorus (TP) leaching were found with the addition of activated carbon and biochar, but total nitrogen (TN) leaching was significantly improved when activated carbon was used as the medium. During a semi-synthetic runoff experiment, the bioretention systems containing two types of fluvial biochar showed relatively better COD and TN control (average mass removal efficiencies and cumulative removal efficiencies) than commercial activated carbon. However, the average TP mass removal efficiency with commercial activated carbon (95% ± 3%) was significantly higher than biochar (48% ± 20% and 56 ± 14%). The addition of biochar in the media increased the nitrogen removal efficiency, and the addition of activated carbon significantly increased the phosphorous removal efficiency. Therefore, both biochar and activated carbon are effective materials for bioretention, and fluvial biochar provides an alternative approach to comprehensively utilize river sediment.
Bacterial community structure and response to nitrogen amendments in Lake Shenandoah (VA, USA)
Authors: Reynoso G. , Smith M. R. , Holmes C. P. , Keelan C. R. , McGrath S. E. , Alvarez G. H. , Coceano M. A. , Eldridge K. A. , Fried H. I. , Gilbert N. E. , Harris M. T. , Kohler L. R. , Modolo C. M. , Murray E. A. , Polisetti S. M. , Sales D. J. , Walsh E. S. , Steffen M. M. 
Published: September 2019

Abstract
Microbial processes are critical to the function of freshwater ecosystems, yet we still do not fully understand the factors that shape freshwater microbial communities. Furthermore, freshwater ecosystems are particularly susceptible to effects of environmental change, including influx of exogenous nutrients such as nitrogen and phosphorus. To evaluate the impact of nitrogen loading on the microbial community structure of shallow freshwater lakes, water samples collected from Lake Shenandoah (Virginia, USA) were incubated with two concentrations of either ammonium, nitrate, or urea as a nitrogen source. The potential impact of these nitrogen compounds on the bacterial community structure was assessed via 16S rRNA amplicon sequencing. At the phylum level, the dominant taxa in Lake Shenandoah were comprised of Actinobacteria and Proteobacteria, which were not affected by exposure to the various nitrogen treatments. Overall, there was not a significant shift in the diversity of the bacterial community of Lake Shenandoah with the addition of nitrogen sources, indicating this shallow system may be constrained by other environmental factors.
Synthesis and Characterization of Copper (II) and Nickel (II) Immobilized on Silica- Coated Copper Ferrite: As Novel Magnetically Reusable Nano Catalysts Towards Reduction of Nitroarenes with NaBH4
Authors: Zeynizadeh Behzad , Sadeghbari Maryam , Pesyan Nader N. 
Published: September 2019

Aim and Objective:
Nowadays, the design, synthesis and application of magnetically nanocomposite
systems have attracted the attention of numerous scientists. The huge surface area and magnetic characteristic
of nanoparticles as well as the inherent potentiality of the used metal species, makes them susceptible to have
different reactivity in chemical reactions. In this context, we therefore encouraged to prepare a new design of
magnetic nanocatalysts as CuFe2O4@SiO2@AAPTMS@Ni(II) and CuFe2O4@SiO2@AAPTMS@Cu(II)
followed by monitoring of their catalytic activities towards reduction of nitroarenes with NaBH4.

Materials and Methods:
Magnetically nanoparticles of CuFe2
O4@SiO2@AAPTMS@Ni(II) and
CuFe2O4@SiO2@AAPTMS@Cu(II) were prepared through a four-step procedure: i) preparation of CuFe2O4
MNPs, ii) coating of CuFe2O4 nucleus by silica-layer using tetraethyl orthosilicate (TEOS), iii) layering of
CuFe2O4@SiO2 MNPs with [3-(2-aminoethylamino)propyl] trimethoxysilane (AAPTMS), and iv) the
complexation of CuFe2O4@SiO2@AAPTMS MNPs with an aqueous solution of Ni(OAc)2·4H2O or
Cu(OAc)2·H2O.

Results:
The catalytic activity of CuFe2O4@SiO2@AAPTMS@Ni(II) and the Cu(II)-analogue towards
reduction of nitroarenes with NaBH4 was studied. The examinations resulted that using a molar ratio of 1:2 for
ArNO2 and NaBH4 in the presence of 20 mg of nanocomposites in H2O under reflux conditions reduces various
aromatic nitro compounds to arylamines in high yields.

Conclusion:
The immobilization of Ni(II) and Cu(II) species on silica-layered CuFe2O4 was investigated.
Magnetically nanoparticles of CuFe2O4@SiO2@AAPTMS@Ni(II) and the Cu(II)-analogue showed the perfect
catalytic activity towards reduction of nitroarenes with NaBH4 in H2O. All reactions were carried out within 2–
15 min to afford aniline products in high yields.
Prevention of Gestational Diabetes Mellitus (GDM) and Probiotics: Mechanism of Action: A Review
Authors: Homayouni Aziz , Bagheri Nahal , Mohammad-Alizadeh-Charandabi Sakineh , Kashani Neda , Mobaraki-Asl Noshin , Mirghafurvand Mojgan , Asgharian Hanieh , Ansari Fereshteh , Pourjafar Hadi 
Published: September 2019

Background: :
Gestational Diabetes Mellitus (GDM) is a health problem that is increasing
around the world.

Introduction::
Prevention of GDM, rather than treatment, could have several benefits in terms of both
health and economic cost. Even a slight reduction in maternal glucose in non-diabetic women, particularly
in women at high risk for GDM, may have significant benefits for pregnancy results and the future
health of off-springs. Probiotics are a relatively new intervention, which are assessed by mothers’
metabolism, and can reduce blood sugar levels, prevent gestational diabetes and reduce the maternal
and fetal complications resulting from it. The aim of this study was to review the studies on the prevention
of gestational diabetes and assess the potential beneficial effects of probiotics on gestational
diabetes and their possible mechanism of action.

Method::
Articles compiled through clinical trials indexed in PubMed, Science Direct, Cochran, and
Medlib between 2000 and 2017, with the keywords probiotics, prevention, and gestational diabetes
mellitus were selected.

Result::
Considering the potential of probiotics in the modulation of gut microbiota, naturalization increases
intestinal permeability, regulation of pro-inflammatory mediators’ secretion and thereby controlling
local and systemic inflammation results in decreasing intestinal permeability, enhancing the
immune system. It likely has the ability to prevent or control diabetes during pregnancy although confirmatory
studies are still needed.

Conclusion::
Experimental and clinical evidence support the supposition that the modulation of the gut
microbiota via probiotic microorganisms could be effective in the prevention of gestational diabetes
mellitus.
Effect of Adding Proprioceptive Exercise to Balance Training in Older Adults with Diabetes: A Systematic Review
Authors: Mohamed Ayman A. , Jan Yih-Kuen 
Published: September 2019

Introduction:
Accidental fall is a serious problem in older adults. The incidence of accidental
fall increases by any dysfunction in the proprioceptive system. The function of the proprioceptive
system usually is much affected in people with Diabetes Mellitus (DM), particularly in older ages.
However, proprioceptive exercise significantly improves the balance control in older adults, no systematic
review demonstrated its effectiveness in improving the balance control in older adults with DM.
Thus, this systematic review was conducted to examine the effectiveness of adding proprioceptive exercise
to any balance training in older adults with DM.

Methods:
A systematic search was performed in five major databases. The inclusion criteria of this
search included older adults with DM, peripheral neuropathy, randomized control trial, and proprioceptive
dysfunction. The exclusion criterion of this search included any study where participants had a history
of a disease that might affect the balance control such as ataxia, stroke, and Parkinsonism. The
outcome of interest was the importance of including proprioceptive exercise in increasing the effectiveness
of balance training in older adults with DM.

Results:
Nine RCTs met the inclusion criteria for this systematic review. Seven studies of these nine
studies included randomization details. Only two studies included the blindness, and only one of them
included double blindness. The description of the withdrawal of participants was shown in eight studies.
All the included studies used a control group and accomplished the homogeny between subjects in
the both groups.

Conclusion:
This systematic review showed that proprioceptive exercise is a vital component that
should be included in any balance training to gain short-term improvement in the balance control in
older adults with DM.
The Value of Corpus Callosum Measurement in the Diagnosis of Cerebral Atrophy
Authors: Ji-Ping Zhao , Chun-Xiao Cui , Chong-Feng Duan , Lei Niu , Xue-Jun Liu 
Published: September 2019

Objective:
The study aimed to investigate the relationship between the corpus callosum
area (CCa) and the degree of cerebral atrophy in patients with cerebral atrophy.

Methods:
119 patients with brain atrophy were grouped according to the degree of brain atrophy.
Median sagittal CCa and intracranial area (ICa) were measured, and the ratio of corpus callosum to
the intracranial area (CCa-ICa ratio) was calculated. The data were analyzed using ANOVA.

Results:
CCa significantly reduced in patients with cerebral atrophy, and the degree of cerebral atrophy
was found to be positively correlated with the degree of reduction in the CCa.

Conclusion:
The reduction in the CCa and the CCa-ICa ratio in the median sagittal can be used as
a reference indicator for the diagnosis and grading of brain atrophy in clinical practice.
Implementation of Neural Network with ALE for the Removal of Artifacts in EEG Signals
Authors: Kumar R. Suresh , Manimegalai P. 
Published: September 2019

Objective:
The EEG signal extraction offers an opportunity to improve the quality of
life in patients, which has lost to control the ability of their body, with impairment of locomotion.
Electroencephalogram (EEG) signal is an important information source for underlying brain
processes.

Materials and Methods:
The signal extraction and denoising technique obtained through timedomain
was then processed by Adaptive Line Enhancer (ALE) to extract the signal coefficient and
classify the EEG signals based on FF network. The adaptive line enhancer is used to update the
coefficient during the runtime with the help of adaptive algorithms (LMS, RLS, Kalman Filter).

Results:
In this work, the least mean square algorithm was employed to obtain the coefficient
update with respect to the corresponding input signal. Finally, Mat lab and verilog HDL language
are used to simulate the signals and got the classification accuracy rate of 80%.

Conclusion:
Experiments show that this method can get high and accurate rate of classification. In
this paper, it is proposed that a low-cost use of Field Programmable Gate Arrays (FPGAs) can be
used to process EEG signals for extracting and denoising. As a preliminary study, this work shows
the implementation of a Neural Network, integrated with ALE for EEG signal processing. The
preliminary tests through the proposed architecture for the activation function shows to be
reasonable both in terms of precision and in processing speed.