Explanatory Parameters Research Articles

Sediment transport prediction in sewer pipes during flushing operation

ABSTRACT This paper presents a novel model for predicting the sediment transport rate during flushing operation in sewers. The model was developed using the Evolutionary Polynomial Regression Multi-Objective Genetic Algorithm (EPR-MOGA) methodology applied to new experimental data collected. Using the new model, a series of design charts were developed to predict the sediment transport rate and the required flushing operation time for several pipe diameters. Accurate results (i.e. sediment transport rates) were obtained when applied to a case study in a combined sewer pipe in Marseille, as reported in the literature. The novelty of the model is the inclusion of the pipe slope, the inflow ‘dam break’ hydrograph, and the sediment properties as explanatory parameters. The new model can be used to predict flushing efficiency and design new flushing cleaning schedules in sewer systems.

Clary Sage Cultivation and Mycorrhizal Inoculation Influence the Rhizosphere Fungal Community of an Aged Trace-Element Polluted Soil.

Soil fungal communities play a central role in natural systems and agroecosystems. As such, they have attracted significant research interest. However, the fungal microbiota of aromatic plants, such as clary sage (Salvia sclarea L.), remain unexplored. This is especially the case in trace element (TE)-polluted conditions and within the framework of phytomanagement approaches. The presence of high concentrations of TEs in soils can negatively affect not only microbial diversity and community composition but also plant establishment and growth. Hence, the objective of this study is to investigate the soil fungal and arbuscular mycorrhizal fungi (AMF) community composition and their changes over time in TE-polluted soils in the vicinity of a former lead smelter and under the cultivation of clary sage. We used Illumina MiSeq amplicon sequencing to evaluate the effects of in situ clary sage cultivation over two successive years, combined or not with exogenous AMF inoculation, on the rhizospheric soil and root fungal communities. We obtained 1239 and 569 fungal amplicon sequence variants (ASV), respectively, in the rhizospheric soil and roots of S. sclarea under TE-polluted conditions. Remarkably, 69 AMF species were detected at our experimental site, belonging to 12 AMF genera. Furthermore, the inoculation treatment significantly shaped the fungal communities in soil and increased the number of AMF ASVs in clary sage roots. In addition, clary sage cultivation over successive years could be one of the explanatory parameters for the inter-annual variation in both fungal and AMF communities in the soil and root biotopes. Our data provide new insights on fungal and AMF communities in the rhizospheric soil and roots of an aromatic plant, clary sage, grown in TE-polluted agricultural soil.

Determinants of Urban Poverty in Ethiopia: The Case of Jimma Town, South West Ethiopia

The objective of this study is to identify determinants of urban poverty in Jimma town. In order to meet the objectives of the study, cross sectional, descriptive and explanatory, research design applied. The sampling technique of the study used stratified and simple random sampling was employed to select households. Information has gathered a sample of 397 household heads were through primary and secondary data. A Logit model was employed and estimated based on the primary data, with the probability of a household being poor as a dependent variable and a set of demographic and socioeconomic variables as the explanatory parameters. By Considering total household consumption and dividing it by the household adult equivalent size, from sample of 397 surveyed household heads, the head count, poverty gap, and severity index of the survey obtained as 66%, 17.8% and 3.16 respectively. The finding revealed that variables that are positively correlated with the probability of being poor are gender, family size, employment/occupation and health/disease incidence of the household. Variables negatively correlated with probability of being poor are: income, educational level, and marital status, age of house hold, housing, house hold residence and saving. The major significance which affected significantly the incidences of poverty in the town are: education, income, age, saving, housing, gender, occupation, family size, previous residence, health and employment. The study concluded that most important determinants of urban poverty in the study area that plays a significant role in affecting incidence poverty are income, education and saving are the major implication to incidence of poverty. Study recommended that strong negative relationship between income, education, saving, housing, and residence with the probability of being poor point out that a need to consider government and non-government organization in designing strategy and policies targeted to curb urban poverty. Keywords: Urban poverty, Jimma Town, House hold-level, analysis DOI: 10.7176/CER/13-4-01 Publication date: June 30 th 2021

Urban sprawl into Natura 2000 network over Europe.

Urban growth is a major threat to biodiversity conservation at the global scale. Its impacts are expected to be especially detrimental when it sprawls into the landscape and reaches sites of high conservation value due to the species and ecosystems they host, such as protected areas. I analyzed the degree of urbanization (i.e., urban cover and growth rate) from 2006 to 2015 in protected sites in the Natura 2000 network, which, according to the Habitats and Birds Directives, harbor species and habitats of high conservation concern in Europe. I used data on the degree of land imperviousness from COPERNICUS to calculate and compare urban covers and growth rates inside and outside Natura 2000. I also analyzed the relationships of urban cover and growth rates with a set of characteristics of Natura sites. Urban cover inside Natura 2000 was 10 times lower than outside (0.4% vs. 4%) throughout the European Union. However, the rates of urban growth were slightly higher inside than outside Natura 2000 (4.8% vs. 3.9%), which indicates an incipient urban sprawl inside the network. In general, Natura sites affected most by urbanization were those surrounded by densely populated areas (i.e., urban clusters) that had a low number of species or habitats of conservation concern, albeit some member states had high urban cover or growth rate or both in protected sites with a large number of species or habitats of high conservation value. Small Natura sites had more urban cover than large sites, but urban growth rates were highest in large Natura sites. Natura 2000 is protected against urbanization to some extent, but there is room for improvement. Member states must enact stricter legal protection and control law enforcement to halt urban sprawl into protected areas under the greatest pressure from urban sprawl (i.e., close to urban clusters). Such actions are particularly needed in Natura sites with high urban cover and growth rates and areas where urbanization is affecting small Natura sites of high conservation value, which are especially vulnerable and concentrated in the Mediterranean region.

The role and determinants of women labor force participation for household poverty reduction in Debre Birhan town, North Shewa zone, Ethiopia

Women participation in economic activities plays a critical role in driving economic development throughout the world. This study aims to analyze the role and determinants of women’s labor force participation for reducing household poverty in the case of Debre Birhan town. To carry out this, the study used a cross-sectional study design. The data was collected by distributing questionnaires to a total of 291 sample households using multi-stage sampling technique. Logistic regression model was employed to analyze the determinants of women labor force participation by the collected data. The binary logit regression result identified that training, exposed to mass media and access to credit and education status of woman were found to be positive and significantly related to the probability of being participate. Moreover, Logistic regression model was employed in order to analyze the effect of woman labor force participation to household poverty reduction, with the probability of a household being poor as a dependent variable and a set of demographic and socioeconomic variables as the explanatory parameters. Based on this, out of the 291 surveyed household heads, 183(62.89%) of them were found poor. The result of this study confirms that women’s participation reduces the household poverty. Therefore, this study recommends that household uses family planning, promotes woman to attend higher education, exposed to mass media, creating public or private daycare centers for child and access to credit for woman. At this juncture both the households and the government should have the joint effort and responsibility to find possible panaceas.

Long-term tending effect on static stability of pure beech (Fagus sylvatica L.) stands

The production stability together with the provision of required functions are the key requirements for the future existence of stable forest stands. Sufficient mechanic stand stability could be developed by the early and long-term thinning where basic tree characteristics, such as stem and crown parameters play the decisive role. We compared selected parameters of static stability in pure beech stands, which have been exposed to heavy low thinning and free-crown thinning with control stands without interventions. Data from twenty-seven long-term research subplots at eight localities across Slovakia were involved in this study. In total 7 693 trees between 30 and 110 years were analysed. Slenderness (h/d ratio), crown length, crown width and crown ratio proved to be the most explanatory parameters for the defining mechanical stability on subplots with free-crown thinning. We found the least favourable results on control subplots. The differences between the subplots with tending (regardless of the tending method) and the control subplots were statistically significant in all studied parameters (P < 0.05).

Examining driver injury severity in left-turn crashes using hierarchical ordered probit models

Objective Few existing studies in the literature devoted efforts to examine the driver injury severity in left-turn crashes. To fill this research gap, this paper aims to provide a comprehensive study of the contributing factors of left-turn crashes and the corresponding injury severities. Methods The hierarchical ordered probit (HOPIT) model is first applied to study driver injury severity in left-turn crashes. The HOPIT model can overcome the limitations of traditional ordered probit models since its thresholds are always positive and ordered. It is a function of unique explanatory parameters that do not necessarily affect the ordered probability outcomes directly. Considering the driving condition during the wintertime could be significantly different from other seasons, this study divided the overall crash dataset into “winter” and “other-season” subsets based on the temperature, snowing condition, and other factors. Results With the “other-season” dataset, results demonstrated that contributing factors, such as young drivers, male drivers, clear, light, and ramp intersection with crossroad, are associated with a decrease in injury severity. On the contrary, factors like drug, alcohol, disregard traffic control device, high-speed limit, the protected left-turn signal, etc., are related to an increase in injury severity. In winter, results revealed that only nine contributing factors are significant to the left-turn crash. Alcohol, disregard traffic control device, nighttime, high-speed limit, head-on collision, and state road are associated with an increase in injury severity. Also, two-vehicle involved, snow, ramp intersection with crossroad are related to a decrease in injury severity. Conclusions The HOPIT model is applied to examine contributing factors of left-turn crashes and the corresponding injury severity, based on left-turn crash records from 2010 to 2017 in Utah. Eighteen significant factors of left-turn crash injury severity are identified in the overall dataset. In seasons rather than winter, the significant factors are almost the same as that of the entire year. In the winter, less significant factors and different patterns are found compared with the overall crashes.

HCN J = 4–3, HNC J = 1–0, H13CN J = 1–0, and HC3N J = 10–9 Maps of Galactic Center Region. II. Physical Properties of Dense-gas Clumps and Probability of Star Formation

Abstract We report a statistical analysis exploring the origin of the overall low star formation efficiency (SFE) of the Galactic central molecular zone (CMZ) and the SFE diversity among the CMZ clouds using a wide-field HCN J = 4–3 map, whose optically thin critical density ( ) is the highest among the tracers ever used in CMZ surveys. Logistic regression is performed to empirically formulate star formation probability of 195 HCN clumps, 13 of which contain star formation signatures. The explanatory parameters in the best-fit model are reduced into the virial parameter without significant contribution from other parameters, whereas the performance of the model without is no better than that using randomly generated data. The threshold is 6, which translates into a volume density ( ) of with the – correlation. The scarcity of the low- clumps, whose fraction to all HCN clumps is 0.1, can be considered as one of the immediate causes of the suppressed SFE. No correlation between the clump size or mass and star formation probability is found, implying that HCN J = 4–3 does not immediately trace the mass of star-forming gas above a threshold density. Meanwhile, star-forming and non-star-forming clouds are degenerate in the physical parameters of the CS = 1–0 clouds, highlighting the efficacy of the HCN = 4–3 line to probe star-forming regions in the CMZ. The timescale of the high- to low- transition is , which is consistent with the tidal compression and X1/X2 orbit transition models but possibly does not fit the cloud–cloud collision picture.

Does the shrub layer act as an intermediary? Effects on abundance of insects and abundances of particular insect orders caught flying in the canopies of deciduous forests in Central Germany

Scientists and society are increasingly becoming aware of loss of insect biodiversity and biomass. The level of biodiversity determines the efficiency of ecological communities to capture essential resources, produce biomass, decompose and recycle nutrients. Relationships between plant and insect diversity can be modified by changes in insect abundance. This study determined the associations between microclimate and diversity of forest plants on overall insect abundance and abundances of different insect orders in the canopy of temperate deciduous forests dominated by Fagus sylvatica L. (European beech; Fagaceae) in Central Germany. Following model selection, a linear mixed model was used to analyse the associations between abiotic factors (air temperature and relative humidity) as well as biotic factors (species richness and cover for the ground, shrub and tree layer) and insect abundance and abundances of insect orders. Within similar strength of evidence, best models were chosen as those with a single explanatory parameter. Significant associations were recorded between abundances of Lepidoptera and Neuroptera and relative air humidity, insect abundance and species richness in the shrub layer, and between abundances of Diptera and Psocoptera and percentage cover of shrubs. Trends in associations were detected between the abundance of Hemiptera and species richness recorded in the shrub layer, and between the abundance of Thysanoptera and the species richness in the ground layer. No significant associations with single explanatory parameters were recorded for the abundances of Coleoptera and Hymenoptera. Phytodiversity, especially that in the shrub layer, were more often associated with the abundances of insect orders than microclimatic factors. The potential importance of the association between shrub layer parameters and the abundance of insects might be based on the shrub layer combining the associations with the ground layer (bottom-up processes) and canopy layer (environmental conditions). In addition, associations between phytodiversity and abundance of insects seem to vary most for Coleoptera and Hymenoptera in which there are markedly different functional groups.

Predicting Audit Opinion in Consolidated Financial Statements with Artificial Neural Networks

The models for predicting audit opinion analyze the variables that affect the probability of obtaining a qualified opinion. This helps auditors to plan revision procedures and control their performances. Despite their apparent relevance, existing models have only focused on the context of individual financial statements and none have referred to consolidated financial statements. The consolidated information is essential for decision-making processes and understanding the true financial situation of a company. Our objective is to provide a new audit opinion prediction model for consolidated financial statements. To this end, a sample of group of Spanish companies was chosen and an artificial neural network technique, the multilayer perceptron, was used. The results show that the developed method managed to predict the audit opinion with accuracy above 86%. Moreover, there exist important differences concerning the most significant variables in the audit opinion prediction for individual accounts, since when using consolidated financial statements, the variables referring to industry, group size, auditor, and board members were converted into the main explanatory parameters of the prediction.

Bulbous perennials precisely detect the length of winter and adjust flowering dates.

In order to identify the most relevant environmental parameters that regulate flowering time of bulbous perennials, first flowering dates of 329 taxa over 33yr are correlated with monthly and daily mean values of 16 environmental parameters (such as insolation, precipitation, temperature, soil water content, etc.) spanning at least 1yr back from flowering. A machine learning algorithm is deployed to identify the best explanatory parameters because the problem is strongly prone to overfitting for traditional methods: if the number of parameters is the same or greater than the number of observations, then a linear model can perfectly fit the dependent variable (observations). Surprisingly, the best proxy of flowering date fluctuations is the daily snow depth anomaly, which cannot be a signal itself, however it should be related to some integrated temperature signal. Moreover, daily snow depth anomaly as proxy performs much better than mean soil temperature preceding the flowering, the best monthly explanatory parameter. Our findings support the existence of complicated temperature sensing mechanisms operating on different timescales, which is a prerequisite to precisely observe the length and severity of the winter season and translate for example, 'lack of snow' information to meaningful internal signals related to phenophases.

Modeling of Head Loss through Deep Bed Sand Filters. (Dept. C ( Public Works ) )

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Regression Model Method for Analyze the Association Rules using Major Parameters

Using the data mining user can extract the information. Frequent itemsets is one of the popular task in data mining. Association Rule Analysis is the task of discovering association rules that occur frequently in a given large data set.The task is to find certain relationships among a set of itemsets in the database. There are two fundamental parameter(measurement) is Support and Confidence.Traditional association rule mining techniques employ predefined support and confidence values. But, it’s observed that specifying minimum support value of the minded rules in advance often leads to either too many or too few rules, which negatively impacts the performance of the overall system.This paper proposes a non-linear regression model using support, confidence and association rules. To predict the number of rules under the given explanatory variables say parameters. Use the R language for the Rules generations and also uses significance test to verify regression coefficients. Using the coefficient test and F-test verify the model

A novel mechanical parameter to quantify the microarchitecture effect on apparent modulus of trabecular bone: A computational analysis of ineffective bone mass.

One of the characteristics of osteoporotic bone is the deterioration of trabecular microarchitecture. Previous studies have shown microarchitecture alone can vary the apparent modulus of trabecular bone significantly independent of bone volume fraction (BV/TV) from morphological and topological perspectives. However, modulus is a mechanical quantity and there is a lack of mechanical explanatory parameters. This study aims to propose a novel mechanical parameter to quantify the microarchitecture effect on the apparent modulus of trabecular bone. Fourteen human female cadaveric vertebrae were scanned with a dual-energy X-ray (DXA) equipment followed by a micro-CT (μCT) system at 18 μm isotropic resolution. Four trabecular bone specimens (3.46 × 3.46 × 3.46 mm) were obtained from each vertebral body and converted to voxel-based micro finite element (μFE) models. The apparent modulus (E) of the μFE model was computed using a linear micro finite element analysis (μFEA). The normalized apparent modulus (E*) was computed as E divided by BV/TV. The relationship between E and BV/TV was analyzed by linear, power-law and exponential regressions. Linear regression was performed between E* and BV/TV. Ineffective bone mass (InBM) was defined as the bone mass with a negligible contribution to the load-resistance and represented by elements with von Mises stress less than a certain stress threshold. InBM was quantified as the low von Mises stress ratio (LSVMR), which is the ratio of the number of InBM elements to the total number of elements in the μFE model. An incremental search technique with coarse and fine search intervals of 10 and 1 MPa, respectively, was adopted to determine the stress threshold for calculating LSVMR of the μFE model. Correlation between E* and LSVMR was analyzed using linear and power-law models for each stress threshold. The threshold producing the highest coefficient of determination (R2) in the correlation between E* and LSVMR was taken as the optimal stress threshold for calculating LSVMR. Linear regression was performed between E and LSVMR. Multiple linear regression of E against both BV/TV and LSVMR was further analyzed. E significantly (p < .001) correlates to BV/TV whereas E* has no significant (p = .75) correlation with BV/TV. Incremental search suggests 59 MPa to be the optimal stress threshold for calculating LSVMR. BV/TV alone can explain 59% of the variation in E using power-law regression model (E = 2254.64BV/TV1.04, R2 = 0.59, p < .001). LSVMR alone can explain 48% of the variation in E using linear regression model (E = 1696.4-1647.1LSVMR, R2 = 0.48, p < .001). With these two predictors taken into consideration, 95% of the variation in E can be explained in a multiple linear regression model (E = 1364.89 + 2184.37BV/TV - 1605.38LSVMR, adjusted R2 = 0.95, p < .001). LSVMR can be adopted as the mechanical parameter to quantify the microarchitecture effect on the apparent modulus of trabecular bone.

Classification of Urban Street Networks Based on Tree-Like Network Features

Urban street networks derive their complexity not only from their hierarchical structure, but also from their tendency to simultaneously exhibit properties of both grid-like and tree-like networks. Using topological indicators based on planning parameters, we develop a method of network division that makes classification of such intermediate networks possible. To quantitatively describe the differences between street network patterns, we first carefully define a tree-like network structure according to topological principles. Based on the requirements of road planning, we broaden this definition and also consider three other types of street networks with different microstructures. We systematically compare the structure variables (connectivity, hierarchy, and accessibility) of selected street networks around the world and find several explanatory parameters (including the relative incidence of through streets, cul-de-sacs, and T-type intersections), which relate network function and features to network type. We find that by measuring a network’s degree of similarity to a tree-like network, we can refine the classification system to more than four classes, as well as easily distinguish between the extreme cases of pure grid-like and tree-like networks. Each indicator has different distinguishing capabilities and is adapted to a different range, thereby permitting networks to be grouped into corresponding types when the indicators are evaluated in a certain order. This research can further improve the theory of interaction between transportation and land use.

Model-based research toward design of innovative materials: molecular weight prediction of bridged polysilsesquioxanes.

Toward the design and manipulation of innovative materials, we propose a new concept called “model-based research (MBR)”. In MBR, measurable physical and chemical properties of materials are mathematically modelled by explanatory parameters obtained by computer simulation from an atomistic point of view. To demonstrate the potential of MBR, we modelled the molecular weights of a series of polysilsesquioxanes with respect to the H2O/silane molar ratio employed for the polymerization of monomers bis(triethoxysilyl)methane, ethane, ethylene, and acetylene (BTES-M, -E1, -E2, and -E3), as an example. The equation y = axn well reproduced the behaviour of the molecular weights of the BTES series, in which a and n were obtained using the calculated molecular parameters for monomers as the explanatory parameters. Detailed understanding and discussion were theoretically possible on the basis of the mathematical model. We predicted the molecular weights of polymers that would be obtained from monomers BTES-P and BTES-Ph with C3H6 and C6H4 as the spacer, respectively, using the mathematical model. Experimental validation of these polymers clearly showed the possibility of qualitative categorization. Our proposed concept, MBR, is a powerful tool to analyse materials science toward innovative materials design.

Determinates of Urban Poverty at Household Level: The Case of Wolaitta Soddo Town, SNNPRS, Ethiopia

Poverty is daily experience of citizens in Ethiopia and the government has implemented different poverty reducing policies and strategies in the intention to reach middle income countries in the coming 7 years. This Study aimed at analyzing the determinants of urban poverty At household level in terms of demographic, economic and social practices in soddo Town. The study was conducted under cross sectional research design. The approach that was used is a mixed approach which makes the use of both quantitative and qualitative methods. Samples of 227 households were drawn from the target population by adopting systematic random sampling technique and 18 of them were discarded from further consideration due to lack of response. Data collecting instruments like questionnaire, semi-structured interview, document analysis and focus group discussions were used to collect data. .A Logistic regression model was employed and estimated based on the primary data, with the probability of a household being poor as a dependent variable and a set of demographic and socioeconomic variables as the explanatory parameters. By making use of Food Energy Intake (FEI) approach the surveyed households are identified as the poor and non-poor. Based on this, Birr 3246 was computed as food poverty line per adult equivalent per month and out of the 209 respondent household heads, 94(45%) were found to be poor. The poverty gap index of 8 percent and poverty severity index of 3 percent were estimated. The variables that are positively correlated with the probability of being poor are family size whose number of members are 5 and above, education, age, sex, saving, electricity connection, unemployment and marital status. The variables that are negatively correlated with the probability of being poor are family size whose numbers of members are less than 5, house tenure, water pipe connection, employment status. These calls for urgent interventions aimed at curbing the problems of the people through creating employment opportunities, family planning, provision of market based short term trainings, empowering females and distribution of social service, improving education services, health services, and creating access to credit facilities need to be promoted for poor urban household in the study area. Keywords: - Poverty, poverty line, poverty incidence, poverty gap, poverty severity DOI : 10.7176/JAAS/60-02 Publication date: January 31 st 2020

Awareness of night brushing and its importance in oral health in parents and among their children

Background: One of the goals of a pediatric dentist is providing awareness among children and their parents about oral hygiene and health. Night brushing is an important step in the prevention of plaque accumulation and caries and is inevitable in maintaining good oral health. Aim: The aim of the study was to assess the awareness of importance of night brushing and its significance on oral health among parents and their children aged 3–13 years in East Bangalore, Karnataka. Materials and Methods: Sample of 300 children was divided into three age range groups, and each group was subdivided into five socioeconomic strata (SES). Separate questionnaires, which were validated by pediatric dentists, were used to record data from the child and the parent. Descriptive analysis of all the explanatory and outcome parameters was done using mean and standard deviation for quantitative variables, frequency, and proportions for categorical variables. SPSS for Windows version 22.0 was used to perform statistical analyses, and the value of P < 0.05 was considered statistically significant. Results: There is an increase in awareness about night brushing in all SES due to increased educational standards and influences of social media and advertisements, but the frequency of practicing the same is questionable. The total child awareness scores in Class I SES demonstrated that 3–6-year age group showed a significant difference as compared with 7–10-year age group (P < 0.001) and 11–13-year age group (P = 0.003). In Class II, 3–6-year age group showed a greater awareness as compared to 7–10-year age group (P = 0.02) and total parent awareness scores in Class III and Class V demonstrated that 3–6-year age group showed significant differences with 7–10-year age group and 11–13-year age group. Conclusion: The awareness of the importance of night brushing is an essential factor affecting oral health. The extent of awareness varies in different SES among the various age groups of children and their parents.

Clinical significance of rectus femoris diameter in heart failure patients.

Heart failure (HF) is often accompanied by skeletal muscle weakness and exercise intolerance, which are known as prognostic factors of HF. Comprehensive evaluation of physical function is important, but it is not commonly conducted because of the lack of equipment or appropriate expertise. Measurement of rectus femoris diameter (RFD) by ultrasound is convenient and noninvasive, but it has not been clarified that RFD could represent physical functions in HF patients. This study evaluated 185 consecutive HF patients and underwent assessment including RFD, grip power (GP), knee extension strength (KES), skeletal muscle index (SMI), nutrition status, cardiopulmonary exercise testing, and New York Heart Association (NYHA) functional class. RFD was related with NYHA class and significantly correlated with GP, KES, SMI, body mass index, pre-albumin level, geriatric nutritional risk index, and peak VO2 (r = 0.631, 0.676, 0.510, 0.568, 0.380, 0.539, 0.527, respectively; p < 0.001). Multivariate regression analysis revealed that estimated glomerular filtration rate (β = 0.551) and RFD (β = 0.326) were predictive factors of peak VO2. Gender, age, brain natriuretic peptide level, left ventricular ejection fraction, and hemoglobin level were the other explanatory parameters. The cut off value of RFD for sarcopenia diagnosis was estimated as 15mm (sensitivity = 0.767 and specificity = 0.808). RFD is a simple and useful marker which reflects skeletal muscle strength/volume, exercise tolerance, nutrition status, and NYHA class. It is also associated with sarcopenia in HF patients.

Adherence to recommendations of Barrett's esophagus surveillance guidelines: a systematic review and meta-analysis.

Guidelines aim to reduce treatment variation and improve quality of care. In the literature there is large variation in the reported rates of adherence to recommendations of surveillance for Barrett's esophagus (BE). The aim of this systematic review was to identify explanatory parameters determining these differences in adherence rates. Embase, Medline Epub, and Web of Science were searched. Studies reporting adherence in at least one of five domains were selected: general domain, surveillance interval, biopsy protocol, landmark identification, and histopathological information. Adherence was expressed as the proportion of endoscopies or endoscopists being in accordance with guideline recommendations. Variation in adherence was evaluated by 1) meta-regression of adherence rates in random effects meta-analysis to define subgroups, and 2) compiling an overview of the most reported explanatory parameters for (non)adherence. 56 studies, including 14 002 BE patients and 4932 endoscopists, were included. Subgroup analysis showed that variation in rates of adherences to surveillance interval recommendations (I 2 = 98 % - 99 %) was explained by difference in country (43 %), by practice type (90 %), and by year of publication (11 %). Variation in adherence to the Seattle protocol was explained by difference in country (14 %). Factors most frequently reported to be associated with better adherence were shorter BE length, salaried employment, surveillance in university hospitals, and dedicated programs. This study provides insight into the variability of rates of adherence to BE surveillance recommendations between studies. Better adherence in university hospitals and dedicated programs indicate that persistent alertness of guidelines is important.