bluuebunny/crossref_metadata_2025_split huggingface dataset:
Does vocabulary knowledge matter in the effectiveness of instructing reading strategies? Differential responses from adolescents with low academic achievement on growth in reading comprehension
Authors: Okkinga M. , Gelderen A. J. S. van , Schooten E. van , Steensel R. van , Sleegers P. J. C. 
Published: December 2022

AbstractPrior studies suggest that teaching reading strategies promotes reading comprehension in adolescents who have difficulties with reading comprehension, yet the results of those studies are mixed. Individual differences in students’ vocabulary knowledge may explain these mixed results. This article examines to what extent vocabulary knowledge influences the effect of a two-year intervention program focused on teaching reading strategies to adolescents with low academic achievement in the Netherlands. We hypothesized that students (N = 310) with different levels of vocabulary knowledge would respond differently to the treatment, given that vocabulary knowledge is an important factor in reading comprehension. Results showed that vocabulary knowledge moderated the effect of the treatment, suggesting that low vocabulary knowledge negatively affected the impact of an intervention focused on reading strategies. Vocabulary knowledge, thus, emerges as a prerequisite for the successful leveraging of a reading strategy intervention. Students with low vocabulary knowledge may experience cognitive overload when attempting to apply newly learned reading strategies while simultaneously trying to find out the meaning of multiple unfamiliar words needed for successful application of reading strategies.
Herkunftsnennung von Täter*innen und Verdächtigen in der Verbrechensberichterstattung
Authors: Klimmt Christoph , Dittrich Anja , Brosius Hans-Bernd , Schmid-Petri Hannah , Schultz Tanjev , Vowe Gerhard 
Published: December 2022

ZusammenfassungJournalist*innen und Kommunikationsverantwortliche bei Sicherheits- und Justizbehörden veröffentlichen zahlreiche Mitteilungen über Straftaten. Häufig besteht dabei die Notwendigkeit zu entscheiden, wie mit einer migrantischen Herkunft von Tatbeteiligten oder ihrer Zugehörigkeit zu von Rassismus betroffenen Gruppen publizistisch umzugehen ist. Diese Entscheidungen können weitreichende Folgen haben und berühren verschiedene Aspekte der Menschenwürde, der gesellschaftlichen Teilhabe und der behördlichen wie medialen Transparenz. Deshalb gibt unser Beitrag eine Empfehlung, ob und wann die Herkunft beziehungsweise Gruppenzugehörigkeit von Verdächtigen oder Täter*innen offengelegt werden sollte. Diese Empfehlung ist wissenschaftlich hergeleitet und im Austausch mit einer interprofessionellen Expert*innengruppe erarbeitet worden. Sie soll keine Vorgaben verkünden, sondern bei einer reflektierten, verantwortungsbewussten und von Sachkenntnis getragenen Einzelfallentscheidung in der täglichen Kommunikationspraxis helfen. Eine „Checkliste“ von Fragen zielt darauf, Medienschaffende und Kommunikationsverantwortliche zusätzlich zu kodifizierten Leitlinien (z. B. Redaktionsstatuten, Ministerialerlassen und Ziffer 12.1 des Pressekodex des Deutschen Presserates) bei Entscheidungen zu unterstützen, die oftmals unter Zeitdruck gefällt werden müssen.
Lymphocytes from B-acute lymphoblastic leukemia patients present differential regulation of the adenosinergic axis depending on risk stratification
Authors: Brum da Silva Nunes Vitória , Kehl Dias Camila , Nathali Scholl Juliete , Nedel Sant’Ana Alexia , de Fraga Dias Amanda , Granero Farias Mariela , Alegretti Ana Paula , Sosnoski Monalisa , Esteves Daudt Liane , Bohns Michalowski Mariana , Oliveira Battastini Ana Maria , Paz Alessandra Aparecida , Figueiró Fabrício 
Published: December 2022

AbstractPurposeAlthough risk-stratified chemotherapy regimens improve B-cell acute lymphoblastic leukemia (B-ALL) clinical outcome, relapse occurs in a significant number of cases. The identification of new therapeutic targets as well as prognostic and diagnostic biomarkers can improve B-ALL patients' clinical outcomes. Purinergic signaling is an important pathway in cancer progression, however the expression of ectonucleotidases and their impact on immune cells in B-ALL lacks exploration. We aimed to analyze the expression of ectonucleotidases in B-ALL patients’ lymphocyte subpopulations.MethodsPeripheral blood samples from 15 patients diagnosed with B-ALL were analyzed. Flow cytometry was used to analyze cellularity, expression level of CD38, CD39, and CD73, and frequency of$${\mathrm{CD}38}^{+}{/\mathrm{CD}73}^{+}$$CD38+/CD73+, and$${\mathrm{CD}39}^{+}{/\mathrm{CD}73}^{+}$$CD39+/CD73+in lymphocyte subpopulations. Plasma was used for cytokines (by CBA kit) and adenine nucleosides/nucleotides detection (by HPLC).ResultsComparing B-ALL patients to health donors, we observed an increase of CD4 + and CD8 + T-cells. In addition, a decrease in CD38 expression in B and Treg subpopulations and an increase in CD39+ CD73+  frequency in Breg and CD8+ T-cells. Analyzing cytokines and adenine nucleosides/nucleotides, we found a decrease in TNF, IL-1β, and ADO concentrations, together with an increase in AMP in B-ALL patients' plasma.ConclusionAs immunomodulators, the expression of ectonucleotidases might be associated with activation states, as well as the abundance of different cellular subsets. We observed a pro-tumor immunity expression profile in B-ALL patients at diagnosis, being associated with cell exhaustion and immune evasion in B-ALL.
Integrated radiomics, dose-volume histogram criteria and clinical features for early prediction of saliva amount reduction after radiotherapy in nasopharyngeal cancer patients
Authors: Zhou Lang , Zheng Wanjia , Huang Sijuan , Yang Xin 
Published: December 2022

AbstractPurposePreviously, the evaluation of xerostomia depended on subjective grading systems, rather than the accurate saliva amount reduction. Our aim was to quantify acute xerostomia with reduced saliva amount, and apply radiomics, dose-volume histogram (DVH) criteria and clinical features to predict saliva amount reduction by machine learning techniques.Material and methodsComputed tomography (CT) of parotid glands, DVH, and clinical data of 52 patients were collected to extract radiomics, DVH criteria and clinical features, respectively. Firstly, radiomics, DVH criteria and clinical features were divided into 3 groups for feature selection, in order to alleviate the masking effect of the number of features in different groups. Secondly, the top features in the 3 groups composed integrated features, and features selection was performed again for integrated features. In this study, feature selection was used as a combination of eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP) to alleviate multicollinearity. Finally, 6 machine learning techniques were used for predicting saliva amount reduction. Meanwhile, top radiomics features were modeled using the same machine learning techniques for comparison.Result17 integrated features (10 radiomics, 4 clinical, 3 DVH criteria) were selected to predict saliva amount reduction, with a mean square error (MSE) of 0.6994 and a R2score of 0.9815. Top 17 and 10 selected radiomics features predicted saliva amount reduction, with MSE of 0.7376, 0.7519, and R2score of 0.9805, 0.9801, respectively.ConclusionWith the same number of features, integrated features (radiomics + DVH criteria + clinical) performed better than radiomics features alone. The important DVH criteria and clinical features mainly included, white blood cells (WBC), parotid_glands_Dmax, Age, parotid_glands_V15, hemoglobin (Hb), BMI and parotid_glands_V45.
Electrical properties of hematite and pure sand synthetic homogeneous mixture
Authors: Gomaa Mohamed Mahmoud 
Published: December 2022

AbstractSubstances' electrical properties react promptly to minor alterations in the specimens (texture). This electrical characteristics response depends on pH and, hence, on the surface charge. In this article, we attempt to keep the synthetic specimens homogeneous. Sand and pure hematite is smashed independently and aggregated (hematite were collected from Eastern Desert, Cairo, Egypt). Electrical parameters were examined at frequencies ranging from 0.1 to 105 Hz (dry, 21 °C). The electrical range of the measured data varies considerably depending on the frequency spectrum, specimens' concentration, constitution, and/or arrangement of the components (texture). There are two conduction areas relying on frequency-dependent conductivity (two slopes). Dielectric permittivity increases linearly with concentration. Dielectric permittivity is rapidly decreasing as the spectrum expands. Jonscher's law is applicable to all electrical characteristics. The hematite conductor concentration changes in the synthetic specimens and accordingly the texture of the specimens. The study of these electrical characteristics may assist in the modeling and simulation of rock electrical properties. The relationships between the ore's nature, mineral compositions, and electrical properties are valuable for exploration methods.
An intelligent approach to improve date palm crop yield and water productivity under different irrigation and climate scenarios
Authors: Dehghanisanij Hossein , Salamati Nader , Emami Somayeh , Emami Hojjat , Fujimaki Haruyuki 
Published: December 2022

AbstractDrought, rising demand for water, declining water resources, and mismanagement have put society at serious risk. Therefore, it is essential to provide appropriate solutions to increase water productivity (WP). As an element of research, this study presents a hybrid machine learning approach and investigates its potential for estimating date palm crop yield and WP under different levels of subsurface drip irrigation (SDI). The amount of applied water in the SDI system was compared at three levels of 125% (T1), 100% (T2), and 75% (T3) of water requirement. The proposed ACVO-ANFIS approach is composed of an anti-coronavirus optimization algorithm (ACVO) and an adaptive neuro-fuzzy inference system (ANFIS). Since the effect of irrigation factors, climate, and crop characteristics are not equal in estimating the WP and yield, the importance of these factors should be measured in the estimation phase. To fulfill this aim, ACVO-ANFIS employed eight different feature combination models based on irrigation factors, climate, and crop characteristics. The proposed approach was evaluated on a benchmark dataset that contains information about the groves of Behbahan agricultural research station located in southeast Khuzestan, Iran. The results explained that the treatment T3 advanced data palm crop yield by 3.91 and 1.31%, and WP by 35.50 and 20.40 kg/m3, corresponding to T1 and T2 treatments, respectively. The amount of applied water in treatment T3 was 7528.80 m3/ha, which suggests a decrease of 5019.20 and 2509.6 m3/ha of applied water compared to the T1 and T2 treatments. The modeling results of the ACVO-ANFIS approach using a model with factors of crop variety, irrigation (75% water requirement of SDI system), and effective rainfall achieved RMSE = 0.005, δ = 0.603, and AICC = 183.25. The results confirmed that the ACVO-ANFIS outperformed its counterparts in terms of performance criteria.
An innovative approach of GSSHA model in flood analysis of large watersheds based on accuracy of DEM, size of grids, and stream density
Authors: Fattahi Alireza Mohebzadeh , Hosseini Khosrow , Farzin Saeed , Mousavi Sayed-Farhad 
Published: December 2022

AbstractDistributed modeling approach may have much better performance and accuracy compared with lumped-parameter hydrologic models. The main goals of this research are: investigating the possibility of combining distributed hydrological models with an one-dimensional hydraulic model and simulating waterways in large watersheds with limited hydrological and hydraulic data. Then performing sensitivity analysis on different parameters in order to identify the parameters containing the major influences on results. In the current research, an innovative approach in Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model, the cross-sections of all 414 waterways in the 3450 km2 Karvandar watershed, used for flow routing calculations, are uniquely extracted. Then, the effect of three essential factors are evaluated. These factors are accuracy of the digital topographic model, cell size of grid network, and density of streams, on the results of GSSHA model simulations. This watershed is located in southeastern Iran, has a dry climate with limited available hydrological data. Results showed that peak discharges obtained from the GSSHA model, developed based on a DEM with a spatial resolution of 12.5 m, are slightly (< 4%) lower than the corresponding values ​​in the GSSHA model with a 30 m DEM resolution. This fact confirms that the use of the topographic model with a lower spatial resolution has no substantial effects on the accuracy of simulation. Also, the peak discharges increased significantly (44% to 57%) by increasing the density of waterways in the GSSHA model. Furthermore, results showed that peak discharge obtained from three models with grid cell sizes of 100, 150, and 200 m (base model), are close together. Comparing with two models of coarser grids (250 and 300 m), significant differences observed, which indicated that the grids larger than 200 m could induce substantial errors in results.
Boosting ensembles for estimation of discharge coefficient and through flow discharge in broad-crested gabion weirs
Authors: Azma Aliasghar , Tavakol Sadrabadi Mohammad , Liu Yakun , Azma Masoumeh , Zhang Di , Cao Ze , Li Zhuoyue 
Published: December 2022

AbstractGabion weirs are environment-friendly structures widely used for irrigation and drainage network purposes. These structures' hydraulic performance is fundamentally different from solid weirs' due to their porosity and the existence of a through-flow discharge. This paper investigates the reliability and suitability of a number of Machine learning models for estimation of hydraulic performance of gabion weirs. Generally, three different Boosting ensemble models, including Gradient Boosting, XGBoost, and CatBoost, are compared to the well-known Random Forest and a Stacked Regression model, with respect to their accuracy in prediction of the discharge coefficient and through-flow discharge ratio of gabion weirs in free flow conditions. The Bayesian optimization approach is used to fine-tune model hyper-parameters automatically. Recursive feature elimination analysis is also performed to find optimum combination of features for each model. Results indicate that the CatBoost model has outperformed other models in terms of estimating the through flow discharge ratio (Qin/Qt) with R2 = 0.982, while both XGBoost and CatBoost models have shown close performance in terms of estimating the discharge coefficient (Cd) with R2 of CatBoost equal to 0.994 and R2 of XGBoost equal to 0.992. Weakest results were also produced by Decision tree regressor with R2 = 0.821 and 0.865 for estimation of Cd and Qin/Qt values.
Climate change impact on hydro-climatic variables of Ribb watershed, Tana sub-basin, Ethiopia
Authors: Tenagashaw Diress Yigezu , Andualem Tesfa Gebrie , Ayele Workineh Tadesse , Belew Amanuel Zewdu 
Published: December 2022

AbstractIn Ethiopia, the Ribb River is one of the tributaries of the Lake Tana sub-basin. Temperature, precipitation, and streamflow would all be affected by climate change in the Ribb watershed. As a result of the disruption of regular hydrological processes, these climate changes have an impact on water resources. The goal of this study was to look into the effects of climate change on the Ribb watershed’s hydro-climatic characteristics. The forecasted climatic data for rainfall and temperature (minimum and maximum) came from the CORDEX (Coordinated Regional Climate Downscaling Experiments) Africa database. Climate change consequences were investigated using RCP 4.5 emission scenarios for the 2021–2060 time range, compared to the 1985–2005 baselines. The observed precipitation and temperature data were used to adjust for bias. The simulation of stream flow was carried out using the semi-distributed and physically based soil and water assessment tool (SWAT). From 1997 to 2003, the model was calibrated, and from 2004 to 2007, it was validated. To determine the trend of the climate variables, trend test analyses were performed on the various time series data. In all of the experiments conducted, the trend test revealed that historical and forecast precipitation recording stations showed statistically negligible trends for all critical values. At a level of 0.05, the historical and prospective maximum and minimum temperature data revealed increasing patterns. In general, the results demonstrated that meteorological conditions cause the flow to decrease over the season. As a result, climate change will have an impact on the Ribb watersheds water resources.
Evaluation of annual total precipitation in the transboundary Euphrates–Tigris River Basin of Türkiye using innovative graphical and statistical trend approaches
Authors: Buyukyildiz Meral 
Published: December 2022

AbstractThe Euphrates–Tigris River Basin (ETRB), one of the largest river basins in the Middle East, is also among the most risky transboundary basins in the world. ETRB has a critical importance for the region both politically and economically due to its location. Evaluating the increasing regional impacts of climate change is even more important for the sustainable management of water and soil resources, especially in transboundary basins such as ETRB. Türkiye is one of the most important riparian countries of the ETRB and the Türkiye part of ETRB constitutes the headwater of the basin. In this study, the temporal variability of the annual total precipitation data for the period 1965–2020 of eighteen stations located in the Türkiye part of the ETRB was investigated. Classical Mann–Kendall (MK) test was used to statistically determine the monotonic trend of precipitation. In addition to the MK method, analyses were carried out with three innovative trend methods, which have the ability to interpret trends both statistically and graphically. These innovative trend methods are Şen innovative trend analysis (Şen-ITA), Onyutha trend test (OTT) and trend analysis with combination of Wilcoxon test and scatter diagram (CWTSD). The results obtained show that there is a decreasing trend in annual total precipitation in ETRB according to all trend methods generally used for the examined period. In addition, the results obtained from the relatively new OTT and CWTSD methods show strong consistency with the results of the other two methods. The advantages such as performing numerical and visual trend analysis with innovative OTT and CWTSD methods, identifying trends in low–medium–high value data and detecting sub-trends have shown that these methods can be used as an alternative to the widely used MK and Şen-ITA.
Synthesis and Characterization of Nylon 6,6-Polyvinyl Alcohol-Based Polyelectrolytic Membrane
Authors: Mahmoud Atia , Saied Mohamed Abu , Naser Abdelrahman , Fahmy Alaa 
Published: December 2022

AbstractThis work presents the preparation and investigation of blended nylon (N)/polyvinyl alcohol (PVA)-based polyelectrolytic membranes that are modified with different concentrations of sulfuric acid (SA), chlorosulfonic acid (CSA), and sulfonated activated carbon (SAC) as a filler. Scanning electron microscopy (SEM) micrographs illustrated good membrane homogeneity, and no cracks or phase separation were detected. Chemical interaction between N, PVA, and other membrane components was confirmed by Raman scattering spectroscopy and Fourier transform infrared (FTIR). In addition, the molecular structure is verified by energy depressive X-ray (EDX). Furthermore, water and methanol uptake, gel fraction, and IEC were determined as functions of varied membrane modification components. The results revealed that increasing the portion of SA, CSA and SAC led to an increase in IEC and ionic conductivity values reached 2.12 meq/g–0.076 S/cm for (N/PVA-4.0% SA-4.0% SAC), respectively, and 2.71 meq/g–0.087 S/cm for (N/PVA-4.0% CSA-4.0% SAC), respectively, while the IEC and ionic conductivity value for non-modified N/PVA membrane was 0.02 meq/g and zero, respectively. Such results enhance the potential feasibility of modified N/PVA electrolytic membranes for fuel cell (FC) applications.
Taguchi Analysis of the Deformation Characteristics of Single-Point Cutting Tool with Micro-Tool Coatings During Orthogonal Machining
Authors: Pai Anand , Shenoy Baloor Satish , Kini Chandrakant R. 
Published: December 2022

AbstractMachining, the art of processing materials, has progressed significantly over the past century. Advances in tool materials look at blended advantages of conventional and modern tool materials through coatings at micro-scales. Tool coatings improve the hot hardness and wear resistance of tool tip and faces. The current study utilizes the Taguchi technique to analyze the deformation response of HSS tools with three different tool coatings—titanium carbide, titanium nitride and titanium aluminum nitride. The coating thicknesses of 10, 50 and 100 $$\upmu$$
μ
m were employed on the rake face and the flank faces of the single-point cutting tool. The response of the tools while machining medium carbon steel 42CrMo4 has been studied using the finite element approach—transient structural analysis module on ANSYS®. The tool deformation was taken up as the key metric.
Who live longer than their age peers: individual predictors of longevity among older individuals
Authors: Nosraty Lily , Deeg Dorly , Raitanen Jani , Jylhä Marja 
Published: December 2022

Abstract
Background
There are a very few studies focusing on the individual-based survival with a long follow-up time.

Aim
To identify predictors and determine their joint predictive value for longevity using individual-based outcome measures.

Methods
Data were drawn from Tampere Longitudinal Study on Aging (TamELSA), a study of individuals’ age 60–89 years (N = 1450) with a mortality follow-up of up to 35 years. Two measures of longevity were used: the longevity difference (LD) and realized probability of dying (RPD), both of which compare each individual’s longevity with their life expectancy as derived from population life tables. Independent variables were categorized into five domains: sociodemographic, health and functioning, subjective experiences, social activities, and living conditions. Linear regression models were used in three steps: bivariate analysis for each variable, multivariate analysis based on backward elimination for each domain, and one final model.

Results
The most important predictors of both outcomes were marital status, years smoked regularly, mobility, self-rated health, endocrine and metabolic diseases, respiratory diseases, and unwillingness to do things or lack of energy. The explained variance in longevity was 13.8% for LD and 14.1% for RPD. This demonstrated a large proportion of unexplained error margins for the prediction of individual longevity, even though many known predictors were used.

Discussion and conclusions
Several predictors associated with longer life were found. Yet, on an individual level, it remains difficult to predict who will live longer than their age peers. The stochastic element in the process of aging and in death may affect this prediction.