Explanatory Parameter Research Articles

Visual prognostic factors following surgery for stage 3 idiopathic epiretinal membrane by Govetto classification.

To investigate the visual prognosis of metamorphopsia in patients undergoing surgery for stage 3 idiopathic epiretinal membrane (ERM) by Govetto classification using preoperative optical coherence tomography (OCT) parameters. Retrospective clinical study. This study included 45 eyes of 45 patients with a minimum follow-up period of 3 months. The best-corrected visual acuity (BCVA) and metamorphopsia score using the M-CHARTS were recorded. Central foveal thickness (CFT), inner nuclear layer thickness (INL), ectopic inner retinal layer thickness (EIFL), outer retinal layer thickness, disruption of the ellipsoid zone, cotton ball sign, and intraretinal cystoid changes were measured based on spectral domain OCT. Preoperative and postoperative values and conditions were compared, and correlations between the preoperative values or conditions and postoperative metamorphopsia scores or BCVA were analyzed. After surgery, the horizontal, vertical, and mean metamorphopsia scores, as well as BCVA, CFT, INL, and EIFL significantly improved (p < 0.001). Using multivariate analysis, only preoperative CFT was a significant explanatory parameter for both the postoperative horizontal metamorphopsia scores and mean values of the postoperative horizontal and vertical metamorphopsia scores (p = 0.019 and p = 0.011, respectively). Age (p = 0.011) and preoperative CFT (p = 0.026) were significant explanatory parameters of postoperative BCVA. Preoperative CFT significantly correlated with postoperative metamorphopsia in patients undergoing surgery for stage 3 idiopathic ERM. This finding might help surgeons predict postoperative visual outcomes and make timely surgical decisions.

Influence of long- and short-range chemical order on spontaneous magnetization in single-crystalline Fe0.6Al0.4 compound thin films

We systematically investigate the long- and short-range chemical order, lattice volume, and spontaneous magnetization in single-crystalline Fe0.6Al0.4 compound thin films. The vapor-quenching method based on a molecular beam epitaxy technique is utilized to fabricate the single-crystalline Fe0.6Al0.4 compound with the different B2 long-range order parameter S. S was varied by the deposition temperature T d, and it increases with increasing T d. The lattice volume V decreased with increasing T d, while the tetragonal distortion, ∼4%, due to epitaxial strain were observed. The changes in S and V were accompanied with the change in the magnetic moment per Fe, μ Fe. μ Fe showed the monotonic decrease as a function of S whereas μ Fe monotonically increases with V. With considering tetragonal distortion, μ Fe–V relationship has a good agreement with the previous reports. The μ Fe–S relationship showed the steep decrease of μ Fe around S∼ 0.6. In contrast to μ Fe–V relationship, μ Fe–S relationship does not match only from ours to previous studies but also among other reports. It implies the statistical number of the nearest-neighbor Fe–Fe bonds, i.e. S, cannot be an enough explanatory parameter. To clarify the structural origin of change in μ Fe, the short-range order (SRO) parameter inferred from the analysis of superlattice diffractions were introduced. They showed the clear difference for the films with high and low μ Fe. The results suggest that the transition from the long- to the SRO state plays the significant role on μ Fe.

Tectonic and geological setting influence hot spring microbiology.

Hydrothermal systems form at divergent and convergent boundaries of lithospheric plates and within plates due to weakened crust and mantle plumes, playing host to diverse microbial ecosystems. Little is known of how differences in tectonic setting influence the geochemical and microbial compositions of these hydrothermal ecosystems. Here, coordinated geochemical and microbial community analyses were conducted on 87 high-temperature (>65°C) water and sediment samples from hot springs in Yellowstone National Park, Wyoming, USA (n = 41; mantle plume setting), Iceland (n = 41, divergent boundary), and Japan (n = 5; convergent boundary). Region-specific variation in geochemistry and sediment-associated 16S rRNA gene amplicon sequence variant (ASV) composition was observed, with 16S rRNA gene assemblages being nearly completely distinguished by region and pH being the most explanatory parameter within regions. Several low abundance ASVs exhibited cosmopolitan distributions across regions, while most high-abundance ASVs were only identified in specific regions. The presence of some cosmopolitan ASVs across regions argues against dispersal limitation primarily shaping the distribution of taxa among regions. Rather, the results point to local tectonic and geologic characteristics shaping the geochemistry of continental hydrothermal systems that then select for distinct microbial assemblages. These results provide new insights into the co-evolution of hydrothermal systems and their microbial communities.

High Wind Speed Prevents the Establishment of the Disease Vector Mosquito Aedes albopictus in Its Climatic Niche in Europe

Environmentally suitable habitats ofAedes albopictus(Ae. albopictus) in Europe are identified by several modeling studies. However, it is noticeable that even after decades of invasion process in Europe, the vector mosquito has not yet been established in all its environmentally suitable areas. Natural barriers and human-mediated transport play a role, but the potential of wind speed to explainAe. albopictus’absences and its inability to establish in its suitable areas are largely unknown. This study therefore evaluates the potential of wind speed as an explanatory parameter of the non-occurrence ofAe. albopictus. We developed a global ecological niche model with relevant environmental parameters including wind speed and projected it to current climatic conditions in Europe.Differences in average wind speed between areas of occurrence and non-occurrence ofAe. albopictuswithin its modeled suitable areas were tested for significance. A second global ecological niche model was trained with the same species records and environmental parameters, excluding windspeed parameters. Using multiple linear regression analyses and a test of average marginal effect, the effect of increasing wind speed on the average marginal effect of temperature and precipitation on the projected habitat suitability was estimated. We found that climatically suitable and monitored areas whereAe. albopictusis not established (3.12 ms-1 ± 0.04 SD) have significantly higher wind speed than areas where the species is already established (2.54 ms-1 ± 0.04 SD). Among temperature-related bioclimatic variables, the annual mean temperature was the most important variable contributing to the performance of both global models. Wind speed has a negative effect on the predicted habitat suitability ofAe. albopictusand reduces false-positive rates in model predictions. With increasing wind speed, the average marginal effect of annual mean temperatures decreases but that of the annual precipitation increases. Wind speed should be considered in future modeling efforts aimed at limiting the spread and dispersal ofAe. albopictusand in the implementation of surveillance and early warning systems. Local-scale data collected from fieldwork or laboratory experiments will help improve the state of the art on how wind speed influences the distribution, flight, and dispersal activity of the mosquito.

Data‐driven approach to construct a fracture toughness master curve for ferritic steels based on tensile properties

Data‐driven approach to construct a fracture toughness master curve for ferritic steels based on tensile properties

Prediction of Young’s modulus of weathered igneous rocks using GRNN, RVM, and MPMR models with a new index

Young’s modulus (YM) of intact rock is an important parameter in the assessment of engineering behaviours of rock masses, and it cannot always be obtained in an economical and practical manner in laboratory experiments. The main purpose of this study is to examine the capability of the minimax probability machine regression (MPMR), relevance vector machine (RVM), and generalised regression neural network (GRNN) models for the prediction of YM. The other aim is to determine the usefulness of a new index, the n-durability index (ndrb), which is based on porosity and the slake durability index. According to the regression analysis performed in this study, the n-durability index as an explanatory parameter performs better than the P-wave velocity (Vp), porosity, and slake durability index in the models, considering the results herein as well as the existing literature. According to regression error characteristic curves, Taylor diagrams, and performance indices, the best prediction model is MPMR, while the worst is the GRNN model. Although GRNN is the worst of the soft computing models, its performance is slightly better than that of the multiple linear regression (MLR) model. According to the results of the study, the MPMR and RVM models with ndrb and Vp are successful tools that can predict the YM of igneous rock materials to different degrees.

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.

Analisis Pengobatan Pasien Menggunakan Model Regresi Logistik Biner

Researcher used patient data spread across two residential areas, namely sector 1 and sector2. The research data consisted of four explanatory variables, namely: the age of the patient, the class ofpatients found in the hospital, the patient’s area of residence, and the findings of the disease suffered by the patient. Class, sector, and disease variables are variables categorized into categories 0 and 1. The researcher considers the dummy variables discussed in the explanatory variable variables. Category 0 indicates that the sample does not meet the criteria in the category. Choosing, category 1 shows that the sample meets the criteria in the category. Next, the researcher will estimate the explanatory parameter variables and dummy variables, then do the partial test to get the parameter significance and model it using the Binary Logistic Regression Model. With the Logistic Regression Model, researcher will calculate the consideration of the patient’s recovery. This probability is used as

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.

Development of Allometric Models for Estimating the Biomass of &amp;lt;i&amp;gt;Sclerocarya birrea&amp;lt;/i&amp;gt; (A.Rich) Hoscht and &amp;lt;i&amp;gt;Boscia senegalensis&amp;lt;/i&amp;gt; (Pers.) Lam. ex Poir.

The objective of this study was to develop allometric models for estimating the biomass of Sclerocarya birrea (A.Rich) Hoscht and Boscia senegalensis (Pers.) Lam. ex Poir. The inventory of these ligneous was carried out at Widou Thiengoly (North of Senegal). The sample consists of 43 individuals of Boscia senegalensis and 15 individuals of Sclerocarya birrea. The selected individuals were dendrometrically characterized before being cut, compartmentalized (trunk, branches, and twigs) and weighed entirely. Simple regression tests were performed to examine the most explanatory dendrometric parameter (x) for biomass (y) according to two types of models: the linear model (y = ax + b) and the polynomial model of degrees 2 (y = ax2 + bx + c). The criteria for selection and validity of the models are based firstly on the tests of normality, nullity, heterogeneity and autocorrelation of the residues. The results showed that the most explanatory dendrometric parameter of the biomass was the crown surface for Boscia senegalensis and the 1.30 m diameter for Sclerocarya birrea of all the tests performed, the second-order Polynomial model is the best predictor of above ground biomass for these two species. Thus, the allometric models established to predict the biomass of these two species are: y = 0.0023x2 + 0.4851x - 0.0519 for Boscia senegalensis and y = 0.35x2 + 10.35x - 12.90 for S. birrea; with very significant correlation coefficients (R2) of 0.85 and 0.94 respectively. These results can be used for a sequestered carbon assessment study and will play a role in monitoring the carbon market in Africa.

Different Degrees of Niche Differentiation for Bacteria, Fungi, and Myxomycetes Within an Elevational Transect in the German Alps.

We used direct DNA amplification from soil extracts to analyze microbial communities from an elevational transect in the German Alps by parallel metabarcoding of bacteria (16S rRNA), fungi (ITS2), and myxomycetes (18S rRNA). For the three microbial groups, 5710, 6133, and 261 operational taxonomic units (OTU) were found. For the latter group, we can relate OTUs to barcodes from fruit bodies sampled over a 4-year period. The alpha diversity of myxomycetes was positively correlated with that of bacteria. Vegetation type was found to be the main explanatory parameter for the community composition of all three groups and a substantial species turnover with elevation was observed. Bacteria and fungi display similar community responses, driven by symbiont species and plant substrate quality. Myxamoebae show a more patchy distribution, though still clearly stratified between taxa, which seems to be a response to both structural properties of the habitat and interaction with specific bacterial and fungal taxa. Finally, we report a high number of myxomycete OTUs not represented in a reference database from fructifications, which might represent novel species.

Biochemical analysis of serum amylase and lipase in patients with type 2 diabetes mellitus

Biochemical analysis of serum amylase and lipase in patients with type 2 diabetes mellitus - IJCBR- Print ISSN No: - 2394-6369 Online ISSN No:- 2394-6377 Article DOI No:- 10.18231/2394-6377.2019.0029, International Journal of Clinical Biochemistry and Research-Int J Clin Biochem Res

Short and Long‐Term Controls on Active Layer and Permafrost Carbon Turnover Across the Arctic

AbstractDecomposition of soil organic matter (SOM) in permafrost terrain and the production of greenhouse gases is a key factor for understanding climate change‐carbon feedbacks. Previous studies have shown that SOM decomposition is mostly controlled by soil temperature, soil moisture, and carbon‐nitrogen ratio (C:N). However, focus has generally been on site‐specific processes and little is known about variations in the controls on SOM decomposition across Arctic sites. For assessing SOM decomposition, we retrieved 241 samples from 101 soil profiles across three contrasting Arctic regions and incubated them in the laboratory under aerobic conditions. We assessed soil carbon losses (Closs) five times during a 1 year incubation. The incubated material consisted of near‐surface active layer (ALNS), subsurface active layer (ALSS), peat, and permafrost samples. Samples were analyzed for carbon, nitrogen, water content, δ13C, δ15N, and dry bulk density (DBD). While no significant differences were observed between total ALSS and permafrost Closs over 1 year incubation (2.3 ± 2.4% and 2.5 ± 1.5% Closs, respectively), ALNS samples showed higher Closs (7.9 ± 4.2%). DBD was the best explanatory parameter for active layer Closs across sites. Additionally, results of permafrost samples show that C:N ratio can be used to characterize initial Closs between sites. This data set on the influence of abiotic parameter on microbial SOM decomposition can improve model simulations of Arctic soil CO2 production by providing representative mean values of CO2 production rates and identifying standard parameters or proxies for upscaling potential CO2 production from site to regional scales.

PENGARUH MODAL SOSIAL DAN SOSIAL EKONOMI TERHADAP NILAI VALUASI EKONOMI AIR BERSIH DI KOTA SURABAYA

ABSTRACT Several factors have been identified as determinants of willingness to pay (WTP), including socioeconomic and environmental elements. The present article aims to investigate the influence of individual social capital on willingness to pay for environmental goods. In particular, through an empirical study, a multi-dimensional measurement of social capital is conducted and its influence on WTP for water quality improvement is explored. According to the results of the survey it is observed that social capital is a significant explanatory parameter of WTP

The association between the maximum step length test and the walking efficiency in children with cerebral palsy.

[Purpose] To improve walking efficiency could be useful for reducing fatigue and extending possible period of walking in children with cerebral palsy (CP). For this purpose, current study compared conventional parameters of gross motor performance, step length, and cadence in the evaluation of walking efficiency in children with CP. [Subjects and Methods] Thirty-one children with CP (21 boys, 10 girls; mean age, 12.3 ± 2.7 years) participated. Parameters of gross motor performance, including the maximum step length (MSL), maximum side step length, step number, lateral step up number, and single leg standing time, were measured in both dominant and non-dominant sides. Spatio-temporal parameters of walking, including speed, step length, and cadence, were calculated. Total heart beat index (THBI), a parameter of walking efficiency, was also calculated from heartbeats and walking distance in 10 minutes of walking. To analyze the relationships between these parameters and the THBI, the coefficients of determination were calculated using stepwise analysis. [Results] The MSL of the dominant side best accounted for the THBI (R2=0.759). [Conclusion] The MSL of the dominant side was the best explanatory parameter for walking efficiency in children with CP.

A new approach for modeling of flow number of asphalt mixtures

Flow number of asphalt-aggregate mixtures is an explanatory parameter for the analysis of rutting potential of asphalt mixtures. In this study, a new model is proposed for the determination of flow number using a robust computational intelligence technique, called multi-gene genetic programming (MGGP). MGGP integrates genetic programming and classical regression to formulate the flow number of Marshall Specimens. A reliable experimental database is used to develop the proposed model. Different analyses are performed for the performance evaluation of the model. On the basis of a comparison study, the MGGP model performs superior to the models found in the literature.

Pilot investigation of two-stage biofiltration for removal of natural organic matter in drinking water treatment

A pilot study employing two parallel trains of two-stage biofiltration, i.e., a sand/anthracite (SA) biofilter followed by a biologically-active granular activated carbon (GAC) contactor, was conducted to test the efficiency, feasibility and stability of biofiltration for removing natural organic matter (NOM) after coagulation in a drinking water treatment plant. Results showed the biofiltration process could effectively remove turbidity (<0.1 NTU in all effluents) and NOM (>24% of dissolved organic carbon (DOC), >57% of UV254, and >44% of SUVA254), where the SA biofilters showed a strong capacity for turbidity removal, while the GAC contactors played the dominant role in NOM removal. The vertical profile of water quality in the GAC contactors indicated the middle-upper portion was the critical zone for the removal of NOM, where relatively higher adsorption and enhanced biological removal were afforded. Fluorescence excitation-emission matrix (EEM) analysis of NOM showed that the GAC contactors effectively decreased the content of humic-like component, while protein-like component was refractory for the biofiltration process. Nutrients (NH4-N and PO4-P) supplementation applied upstream of one of the two-stage biofiltration trains (called engineered biofiltration) stimulated the growth of microorganisms, and showed a modest effect on promoting the biological removal of small non-aromatic compositions in NOM. Redundancy analysis (RDA) indicated influent UV254 was the most explanatory water quality parameter for GAC contactors’ treatment performance, and a high load of UV254 would result in significantly reduced removals of UV254 and SUVA254.

Anthropometrics and Body Composition in East African Runners: Potential Impact on Performance

Maximal oxygen uptake (V̇O2max), fractional utilization of V̇O2max during running, and running economy (RE) are crucial factors for running success for all endurance athletes. Although evidence is limited, investigations of these key factors indicate that East Africans' superiority in distance running is largely due to a unique combination of these factors. East African runners appear to have a very high level of RE most likely associated, at least partly, with anthropometric characteristics rather than with any specific metabolic property of the working muscle. That is, evidence suggest that anthropometrics and body composition might have important parameters as determinants of superior performance of East African distance runners. Regrettably, this role is often overlooked and mentioned as a descriptive parameter rather than an explanatory parameter in many research studies. This brief review article provides an overview of the evidence to support the critical role anthropometrics and body composition has on the distance running success of East African athletes. The structural form and shape of these athletes also has a downside, because having very low BMI or body fat increases the risk for relative energy deficiency in sport (RED-S) conditions in both male and female runners, which can have serious health consequences.

Fetishes and factishes: Durkheim and Latour.

This paper defends the concept of 'fetishism' as an explanatory parameter in sociological theorizing on Durkheimian grounds, while at the same time paying due attention to important insights regarding the role of objects in social life, originating from Actor-Network Theory (ANT). It critically assesses the current critique of the concept of fetishism propagated by ANT protagonist Bruno Latour. Latour and suggests a compromise between these two 'schools'. First, to place the paper firmly in context, I analyse some examples of modern fetishism and outline the themes of the ensuing discussion. Next, I turn to Durkheim, seeking to develop a distinct interpretation of the concept of the social and of fetishism, and then point to some of Durkheim's shortcomings and attempt to make room for Latourian perspectives. Finally, I critically assess Latour's dismissal of forms of social 'explanation' and of the concept of fetishism.

PENGARUH MODAL SOSIAL DAN SOSIAL EKONOMI TERHADAP NILAI VALUASI EKONOMI AIR BERSIH DI KOTA SURABAYA

Several factors have been identified as determinants of willingness to pay (WTP), including socioeconomic andenvironmental elements. The present article aims to investigate the influence of individual social capital onwillingness to pay for environmental goods. In particular, through an empirical study, a multi-dimensionalmeasurement of social capital is conducted and its influence on WTP for water quality improvement is explored.According to the results of the survey it is observed that social capital is a significant explanatory parameter ofWTP