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In this study, it was aimed to predict elementary education teacher candidates' achievements in "Science and Technology Education I and II" courses by using artificial neural networks. It was also aimed to show the independent variables importance in the prediction. In the data set used in this study, variables of gender, type of education, field of study in high school and transcript information of 14 courses including end-of-term letter grades were collected. The fact that the artificial neural network performance in this study was R=0.84 for the Science and Technology Education I course, and R=0.84 for the Science and Technology Education II course shows that the network performance overlaps with the findings obtained from the related studies.

Copyright of Architecture & Life Journal / Kocaeli Üniversitesi Mimarlık ve Yaşam Dergisi is the property of Architecture & Life Journal / Kocaeli Universitesi Mimarllik ve Yasam Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study predicts the number of correct answers given by pre-service classroom teachers in Civil Servant Recruitment Examination's (CSRE) educational sciences test based on their high school grade point averages, university entrance scores, and grades (mid-term and final exams) from their undergraduate educational courses. This study was therefore designed by using a general survey model. The participants were 219 graduates of the departments of classroom teacher education from the education faculties of two different state universities. Artificial neural networks (ANNs) were used to predict the numbers of correct answers from the CSRE educational sciences test. As a result of different trials, the correlation between the predicted and actual numbers of correct answers was examined, and 10 ANN models were included in the study. Statistically, significant positive correlations were found between the numbers of correct answers predicted by the ANN and the students' actual correct answers in the CSRE. The highest loading was r = 0.63 (p < 0.01), and the lowest was r = 0.43 (p < 0.05).

The current study investigated which dimensions of scientific process are capitalized on by elementary school third graders to explain the concept of science at conceptual level. The study was conducted by using "Basic Qualitative Research", one of the qualitative research approaches with the participation of 225 elementary school third graders. Totally 46 codes used by the students to explain the concept of science were formed and these codes were classified under seven themes. At the end of the study, it was concluded that the students mostly used the codes classified under the theme of scientific process to explain the concept of science. The findings of the study are believed to make some important contributions to the development of the teaching program of the Science Course to be given to elementary school third grade as of 2014-2015 school year and to the implementation of this program by eliciting the current state of students.

Copyright of Mehmet Akif Ersoy University Journal of Education Faculty is the property of Mehmet Akif Ersoy Universitesi Egitim Fakultesi Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: Non-metastatic esophageal squamous cell carcinoma (ESCC) patients are treated with neoadjuvant chemoradiotherapy (CRT) followed by surgery. Older patients may have treatment-related toxicity at higher rates. We presented our experience regarding CRT followed by surgery on survival in older ESCC patients. Methods: Older ESCC patients diagnosed between 2009-2021 were included. Overall survival (OS) estimates were calculated by Kaplan-Meier analyses and compared by Log-rank tests. Effects of ECOG performance status and age groups on survival were also presented. Results: A total of 66 older ESCC patients were included. The median duration of follow-up was 62.3 months. The median OS of patients who were treated with surgery was significantly higher than those who were treated with CRT alone (48+, CI 95%: - vs. 14.1 months, CI 95%: 9.3-18.8, respectively, p=0.005). The median OS of patients who underwent surgery was significantly higher after adjusting by ECOG performance status and age groups than those who were treated with CRT alone (adjusted p=0.008 for ECOG and adjusted p=0.011 for age groups at diagnosis). Conclusion: Surgery after CRT improves survival in older ESCC patients compared to CRT alone. Therefore, surgery should not be avoided in older patients solely due to patient age. [ABSTRACT FROM AUTHOR]

Background: Malnutrition is a frequent issue in esophageal cancer (EC). The Controlling Nutritional Status (CONUT) Score has been established as a prognostic indicator in EC patients who underwent surgery. We aimed to investigate the role of the CONUT Score in EC patients treated with chemoradiotherapy (CRT). Methods: The trial included 101 non-metastatic EC patients. Receiver operating characteristic (ROC) curve analyses were used to determine cut-off values for the CONUT Score and other indices. Cox regression analyses were performed to determine prognostic markers. Results: Of 101 patients, 59.4% (n = 60) and 40.6% (n = 41) of patients were treated with CRT alone and CRT plus surgery, respectively. ROC curve analyses determined an optimal cut-off for CONUT Score in overall survival (OS), which was 3.5 (AUC = 0.63, CI 95%: 0.51-0.76, P = 0.05). The sensitivity and specificity of CONUT were 66% and 61%, respectively. Low CONUT (≤3.5) patients had significantly longer median OS than high CONUT (>3.5) patients (57.1 vs. 23 months; P = 0.009). Multivariate regression analysis revealed a CONUT Score hazard ratio (HR) of 1.96 for OS (CI 95%: 1.03-3.75, P = 0.04). Conclusion: The CONUT Score might be a useful prognostic tool in EC patients treated with CRT. Appropriate nutritional support might provide a better prognosis, which underlines the importance of multidisciplinary assessment of malnutrition in EC patients. [ABSTRACT FROM AUTHOR]

Aim: Systemic inflammation has been associated with chemoresistance and prognosis in solid tumors. Systemic immune‐inflammation index (SII) is a novel marker derived from complete blood count. We investigated whether differences between SIIs measured before and after neoadjuvant chemotherapy (NACT) are associated with tumor regression grade (TRG) and survival in gastric and gastroesophageal junction (GEJ) cancer patients. Methods: Records of gastric and GEJ cancer patients treated with NACT in two centers were evaluated retrospectively. Patients were categorized according to difference between pre‐ and post‐NACT SII values (ΔSII). Association between clinicopathological factors and TRG was analyzed using logistic regression method. Predictors of disease‐free and overall survival (DFS and OS) were determined with Cox regression models. Results: The study included 140 patients. Patients with ΔSII<0 were more likely to achieve TRG 0/1 (45.2% vs. 19.1%, p = 0.003) and ΔSII<0 was an independent predictor of TRG 0/1 (OR = 6.05, p<0.001). DFS and OS of patients with ΔSII<0 were also significantly longer (p = 0.031 and p = 0.006, respectively). After adjustment for other variables, ΔSII≥0 was an independent prognostic factor for OS (Hazard ratio (HR) = 2.13, p = 0.008). Conclusions: Changes in SII, which is a low‐cost and easily accessible marker, may be used to estimate prognosis, individualize postoperative treatment and optimize surveillance in gastric and GEJ cancer patients treated with NACT. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Kirsehir Education Faculty is the property of Journal of Kirsehir Education Faculty and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aimed to investigate the prediction level of science success in high school entrance exams (HSEE/LGS) using artificial neural networks (ANNs) by associating students' success in science classes from the 4th-grade elementary level. The Pearson Moment Product Correlation analysis results were analyzed using the SPSS program to examine the connection between students' performance on the LGS science subtest and their academic achievement in science. In the MATLAB program, artificial neural network modeling performance was examined to understand the level of prediction. The data sets were obtained from the electronic school system of the Ministry of National Education for the 4th to 8thgrades of 1027 students graduating from 24 schools in 17 districts of Bursa in the 2017-2018 academic year and entered the 2018 LGS and LGS result documents without personal information. When the correlations between the LGS science sub-test and science test success were examined (p <.001), the highest and lowest correlations were found in the 8th-grade science exams (r = .70) and the 4th-grade ones (r=.57), respectively. The highest performance values were learning R=.80, verification R=.74, and test R=.75, RMSE=2.35 at the network architecture, generated in the second sub-problem and the trained network with 845 student data. A high-level relationship with r=.75 (p<.001) using the data of 182 students was obtained, while the correct numbers of simulated real LGS science sub-tests compared with the correct numbers predicted by the computer after the training process of the network. In addition, it was obtained that 124 students out of 182 were correctly estimated in the [+ 2, -2] error value range. [ABSTRACT FROM AUTHOR]

A proof-of-concept demonstration of through-wall sensing with microwave radiometry is described. A multifrequency microwave radiometer with 37 channels from 2.1 to 17.35 GHz was used in two experiments to observe objects through a cinder block wall of approximately 20-cm thickness. Measured data show the clear ability of the radiometer to detect thermal contrasts on the interior of the wall. A discussion of the basic physical processes involved in the measurement is provided. When compared with active systems, microwave radiometry for through-wall sensing faces significant challenges, including limitations in ranging, horizontal resolution, and corruption by radio-frequency interference, but also provides complementary capabilities, particularly with regard to thermal information. Further consideration of microwave radiometry appears warranted for applications where thermal information is of interest. Index Terms--Microwave radiometry, remote sensing.

Objective: High-grade serous ovarian carcinoma (HGSC) is one of the major tumors of the gynecological system with a poor survival rate and variable microscopic appearance. It was suggested that SET (solid, pseudo-endometrioid and transitional-like) morphology in ovarian HGSC is predictably associated with BRCA deficiencies. In this study, we investigated the microscopic patterns and some immunohistochemical markers predicting the prognosis of serous carcinoma. Material and Method: We re-evaluated 305 HGSC ovarian resections morphologically and calculated the SET morphology percentages for each case. Morphological and immunohistochemical data correlated with the survival and post-treatment disease progression data. Results: The median age at diagnosis was 57 years and the median follow-up period was 3.1 years. The median overall survival (OS) of ovarian carcinoma in SET-predominant tumors (n=60) was 81 months, while for tumors with SET non-dominant morphology (n=63) and non-SET morphology (n=182) it was 59.7 and 44.7 months, respectively. Conclusion: Predominant (more than 50%) SET morphology was significantly associated with increased survival rates of HGSC. Immunohistochemically, p53, ERCC1, ER, and PR antibodies were applied and only PR antibody positivity was found to be associated with borderline statistical significance for increased survival rates. Our results suggest that SET morphology may be a potential predictive and prognostic marker in managing the treatment strategies of HGSC. [ABSTRACT FROM AUTHOR]

A derivation of the fourth-order term in the small-slope approximation (SSA) of thermal emission from the sea surface is presented. It is shown that this term has the form of a fourfold integration over a product of two sea spectra for a Gaussian random process sea, thereby describing emission 'interaction' effects among pairs of sea waves. An approximation for 'long-long' wave interactions (i.e., the optical limit) is considered and shown to match the physical optics theory. Interaction effects between 'long' and 'short' waves are also considered, both through numerical and approximate evaluations of the fourth-order theory. The approximation developed has a form similar to an expanded 'two-scale' model and enables comparisons of short-wave 'tilting' effects between the two models in terms of spectrum independent 'weighting' functions. The weighting functions obtained are found to be similar, but not identical, for the SSA and two-scale theories. In addition, azimuthal harmonics from the fourth-order SSA expansion of long-short wave interactions for a particular sea-surface model are compared against the full fourth-order theory and the two-scale model. Results again show the SSA and two-scale models to yield similar, but not identical, predictions. Index Terms--Microwave radiometry, rough-surface scattering, thermal emission.