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Examination of Aggression and School Attitudes of High School Students Exposed to Teacher Violence and Peer Bullying
No full texthis study primarily aimed to examine whether high school students’ exposure to teacher violence and peer bullying predicts their aggressive behaviors and attitudes toward school. The study group of the research included a total of 880 secondary education students (473 girls, 407 boys) (mean age: 16.26) studying in different cities of Turkey. The research utilized measures including “Personal Information Form,” “Teacher Violence Scale,” “Peer Bullying Scale Adolescent Form,” “Aggressive Behavior Scale,” and “School Attitude Scale.” The analyses performed showed that the variables exposure to teacher violence (β=.304) and peer bullying (β=.281) explained 26% of students’ aggression variance. Similarly, exposure to teacher violence (β= −.302) and exposure to peer bullying (β= −.109) predicted students’ school attitudes by 14%. The findings were discussed in line with the relevant literature
Relationship between Person-Environment Fit Types and Turnover Intention: A Moderated Mediation Model
No full textIn this study, drawing on Hobfoll's Conservation of Resources (COR) Theory, we tested a moderated mediation model that investigates person-organization (PO) fit as the mediator and person-job (PJ) fit as the moderator in the relationship between person-supervisor (PS) fit and turnover intention. Data were collected from 232 bank employees in Turkey by using a survey method. Consistent with hypothesized conceptual scheme, results showed that PO fit mediated the relationship between PS fit and turnover intention. Furthermore, moderated mediation results indicate that PJ fit not only moderated the relationship between PS fit and PO fit but also reinforced the indirect effect of PS fit on turnover intention (via PO fit). We argue that indirect effect of PS fit on turnover intention through PO fit was stronger for employees with high job fit than for employees with low job fit. The theoretical and practical implications, limitations, and future research directions are also discussed
Evaluation of nutritional status in pediatric intensive care unit patients: the results of a multicenter, prospective study in Turkey
No full textntroductionMalnutrition is defined as a pathological condition arising from deficient or imbalanced intake of nutritional elements. Factors such as increasing metabolic demands during the disease course in the hospitalized patients and inadequate calorie intake increase the risk of malnutrition. The aim of the present study is to evaluate nutritional status of patients admitted to pediatric intensive care units (PICU) in Turkey, examine the effect of nutrition on the treatment process and draw attention to the need for regulating nutritional support of patients while continuing existing therapies.Material and MethodIn this prospective multicenter study, the data was collected over a period of one month from PICUs participating in the PICU Nutrition Study Group in Turkey. Anthropometric data of the patients, calorie intake, 90-day mortality, need for mechanical ventilation, length of hospital stay and length of stay in intensive care unit were recorded and the relationship between these parameters was examined.ResultsOf the 614 patients included in the study, malnutrition was detected in 45.4% of the patients. Enteral feeding was initiated in 40.6% (n = 249) of the patients at day one upon admission to the intensive care unit. In the first 48 h, 86.82% (n = 533) of the patients achieved the target calorie intake, and 81.65% (n = 307) of the 376 patients remaining in the intensive care unit achieved the target calorie intake at the end of one week. The risk of mortality decreased with increasing upper mid-arm circumference and triceps skin fold thickness Z-score (OR = 0.871/0.894; p = 0.027/0.024). The risk of mortality was 2.723 times higher in patients who did not achieve the target calorie intake at first 48 h (p = 0.006) and the risk was 3.829 times higher in patients who did not achieve the target calorie intake at the end of one week (p = 0.001). The risk of mortality decreased with increasing triceps skin fold thickness Z-score (OR = 0.894; p = 0.024).ConclusionTimely and appropriate nutritional support in critically ill patients favorably affects the clinical course. The results of the present study suggest that mortality rate is higher in patients who fail to achieve the target calorie intake at first 48 h and day seven of admission to the intensive care unit. The risk of mortality decreases with increasing triceps skin fold thickness Z-score
Using machine learning algorithms to identify predictors of social vulnerability in the event of a hazard: Istanbul case study
No full textWhat extent an individual or group will be affected by the damage of a hazard depends not just on their exposure to the event but on their social vulnerability - that is, how well they are able to anticipate, cope with, resist, and recover from the impact of a hazard. Therefore, for mitigating disaster risk effectively and building a disaster-resilient society to natural hazards, it is essential that policy makers develop an understanding of social vulnerability. This study aims to propose an optimal predictive model that allows decision makers to identify households with high social vulnerability by using a number of easily accessible household variables. In order to develop such a model, we rely on a large dataset comprising a household survey (n = 41 093) that was conducted to generate a social vulnerability index (SoVI) in Istanbul, Turkiye. In this study, we assessed the predictive ability of socio-economic, socio-demographic, and housing conditions on the household-level social vulnerability through machine learning models. We used classification and regression tree (CART), random forest (RF), support vector machine (SVM), naive Bayes (NB), artificial neural network (ANN), k-nearest neighbours (KNNs), and logistic regression to classify households with respect to their social vulnerability level, which was used as the outcome of these models. Due to the disparity of class size outcome variables, subsampling strategies were applied for dealing with imbalanced data. Among these models, ANN was found to have the optimal predictive performance for discriminating households with low and high social vulnerability when random- majority under sampling was applied (area under the curve (AUC): 0.813). The results from the ANN method indicated that lack of social security, living in a squatter house, and job insecurity were among the most important predictors of social vulnerability to hazards. Additionally, the level of education, the ratio of elderly persons in the household, owning a property, household size, ratio of income earners, and savings of the household were found to be associated with social vulnerability. An open-access R Shiny web application was developed to visually display the performance of machine learning (ML) methods, important variables for the classification of households with high and low social vulnerability, and the spatial distribution of the variables across Istanbul neighbourhoods. The machine learning methodology and the findings that we present in this paper can guide decision makers in identifying social vulnerability effectively and hence let them prioritise actions towards vulnerable groups in terms of needs prior to an event of a hazard
Effectiveness of cold application and lavender oil on pain during drain removal: A randomized clinical trial
No full textBackground and Aim: Analgesics are frequently used to prevent acute pain while removing the drain. Additional non-pharmacological methods have come to the agenda as a result of the fact that the pain cannot be fully controlled, and the pharmacological treatment response is variable. Our research was intended to determine the effectiveness of lavender aromatherapy and cold application in controlling pain during drain removal procedure. Materials and Methods: The sample of the prospective randomized controlled study consisted of 121 patients. Patient data were collected using the introductory information form and the numerical pain scale. Four groups of patients were formed (lavender oil, oxygen, cold application, control), respectively. In all groups, vital signs and pain levels were evaluated before the drain removal procedure, as soon as and 15 minutes after it was withdrawn. Results: Within the limits of study, lavender aromatherapy and cold application to the drainage area were found to be effective in reducing pain during drainage. When the effect on vital signs was evaluated, it was found that the pre-procedure systolic blood pressure was higher in both the lavender group and the cold application group than the post-procedure systolic blood pressure, and the respiratory rate was higher in the control group during the procedure. Conclusions: According to the study, it was found that applying lavender and cold application to the patients before the drainage procedure was effective in controlling pain
Electrical and photoresponse properties of metal–polymer–semiconductor device with TMPTA interface material
No full textis study presents the pioneering fabrication of a metal–polymer–semiconductor (MPS) device, where trimethylolpropane triacrylate (TMPTA) was employed as the interface material for the first time. TMPTA offers significant advantages in terms of optoelectronic device fabrication and encapsulation, owing to its high light transmittance. The device was thoroughly characterized employing scanning electron microscopy (SEM) and electrical measurements, including current–voltage (I– V) and capacitance–voltage (C– V) analyses. The fabricated device demonstrated a notably elevated rectification ratio of 3000 along with a low reverse bias saturation current. Subsequently, the ideality factor and junction barrier potential were calculated to be 3.65 and 0.79 eV, respectively. Due to the low viscosity of the TMPA interface material, it was calculated that a series resistance of 6.7 kΩ calculated in the forward-bias region as a result of obtaining a thickness of approximately 200 nm by means of employing SEM measurements. The photodiode behavior of the device was shown through I– V measurements conducted under diverse illumination intensities. The observed exponential relationship between the photocurrent and illumination intensity strongly suggests the prevalence of the nanomolecular reassembly mechanism within the device. Additionally, frequency- and voltage-dependent capacitance measurements unveiled the substantial impact of state densities and series resistance effects at the interfaces of semiconductor–polymer and metal–semiconductor, resulting in noteworthy alterations in the device’s performanc
Modified Local Linear Estimators in Partially Linear Additive Models with Right-Censored Data Based on Different Censorship Solution Techniques
No full textThis paper introduces a modified local linear estimator (LLR) for partially linear additive models (PLAM) when the response variable is subject to random right-censoring. In the case of modeling right-censored data, PLAM offers a more flexible and realistic approach to the estimation procedure by involving multiple parametric and nonparametric components. This differs from the widely used partially linear models that feature a univariate nonparametric function. The LLR method is employed to estimate unknown smooth functions using a modified backfitting algorithm, delivering a non-iterative solution for the right-censored PLAM. To address the censorship issue, three approaches are employed: synthetic data transformation (ST), Kaplan-Meier weights (KMW), and the kNN imputation technique (kNNI). Asymptotic properties of the modified backfitting estimators are detailed for both ST and KMW solutions. The advantages and disadvantages of these methods are discussed both theoretically and practically. Comprehensive simulation studies and real-world data examples are conducted to assess the performance of the introduced estimators. The results indicate that LLR performs well with both KMW and kNNI in the majority of scenarios, along with a real data exampl
Phenolic Composition, Anti-Biofilm, Anti-Quorum Sensing, Antioxidant and Enzyme Inhibitory Activities of Pteleopsis Suberosa (Combretaceae) Leaves
No full textP. suberosa is a multipurpose medicinal plant in West and Central Africa. Fourteen phenolic compounds were identified in the P. suberosa leaves extract using HPLC-DAD and gallic acid (175.10 & PLUSMN;0.42 & mu;g/g) was the most abundant. The total phenolic content was 112.16 & PLUSMN; 0.33 mg GAE/g DW while the total flavonoid content was 36.10 & PLUSMN;0.58 mg QE/g DW. Minimal inhibitory concentration (MIC) values for antimicrobial activity were 0.3125 mg/mL and 1.25 mg/mL on S. aureus and E. faecalis respectively and 2.5 mg/mL and 0.3125 mg/mL on E. coli and S. typhi respectively. Biofilm inhibition evaluated at sub-MIC concentrations revealed that gram-negative biofilms were more susceptible to P. suberosa extract than gram-positive ones and E. coli biofilms were the most susceptible. The extract inhibited violacein production and quorum sensing with inhibition zones varying from 17.0 & PLUSMN;0.5 mm at MIC to 12.0 & PLUSMN;0.1 mm at MIC/4. The extract showed good antioxidant capacity and was more active in the DPPH & BULL; assay than the two standards & alpha;- tocopherol and BHA used. In the ABTS & BULL;+ and CUPRAC assays, the activity of the extract was greater than that of & alpha;-Tocopherol and very close to that of BHA. The extract showed potential to alleviate Alzheimer's disease by inhibiting acetylcholinesterase and butyrylcholinesterase as well as antidiabetic activity by inhibiting & alpha;-amylase and & alpha;-glucosidase. This is an open-access article distributed under the terms of the Creative Commons Attribution -Non Commercial-Share Alike 4.0 License, which allows others to remix, tweak, and build upon the work non commercially, as long as the author is credited and the new creations are licensed under the identical terms
A Novel Microwave Noise Generator Using Multiple Zener Diodes Connected in Series
No full textA novel microwave noise generator circuit using multiple Zener diodes connected in series was designed and tested. Measurements are presented up to 6 GHz. It is presented in this letter that when the number of series Zener diodes increases, the amount of noise power generated also increases across the band of interest. However, the increase of noise power from one-zener to two-zener configuration and from two-zener to three-zener configuration is not uniform. Measurements were limited to three zeners connected in series due to available high-voltage dc power supply.
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Influence of two-step austempering at different temperatures on mechanical and microstructural properties of AISI 9254 high silicon steel
No full textThis study was undertaken to understand the effects of two-step austempering treatment on an AISI 9254 high silicon steel towards tailoring the properties as desired while simultaneously employing the benefits of high and low austempering temperatures. The samples were initially austenitized at 850°C for 20 min, followed by austempering in a salt bath at the temperatures of 250–270–290°C for 20 min during the first stage. Subsequently, a second stage austempering was carried out by raising the temperature of the salt bath to 300°C at an average heating rate of 0.5°C/min, and the samples were kept in the salt bath for achieving a total austempering time of 120 min including the heating time. A conventional single-stage austempering was also conducted for comparison purposes, in which the austenitization temperature, the austempering temperatures and total time (stage I and stage II, i.e. 120 min) were kept the same for the benchmark samples. In the characterization studies, tensile test, hardness test, XRD analysis, optical microscope and field emission-scanning electron microscope (FE-SEM) equipped with EBSD detector were utilized. The findings of this study indicated that lowering the austempering temperature resulted in refining the structure with a decrease in the amount of austenite. According to the carbon content analysis through XRD patterns, the two-step austempering processes appeared to have considerably increased the carbon content of the austenite irrespective of austempering temperature. The best ultimate tensile strength (U.T.S) of 2194 MPa was achieved in the conventionally austempered sample at the lowest temperature of 250°C, while the best yield strength (Y.S.) of 1753 MPa was reached in the stepped austempered sample initially at 250°C followed by 300°C. In general, two-step austempering process led to a higher yield strength while affecting the ultimate tensile strength and total elongation depending on the austempering temperature