Kilis 7 Aralik Üniversitesi

The production of high-quality and safe milk is closely associated with the udder health of dairy cows. While there are many mastitis diagnostic tests/methods available, choosing the most appropriate diagnostic test for a sustainable udder health control program could be a challenge. This study was aimed at selecting tests for the screening of subclinical mastitis on small- and large-scale dairy farms in Türkiye, using multi-criteria decision-making methods. An integrated approach employing the analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) together was used to select subclinical mastitis screening tests for on-farm use. While the AHP determines the weights of the evaluation criteria, the TOPSIS provides a final ranking. Nine different subclinical mastitis screening (SCM) methods (DeLaval somatic cell counter, PortaSCC test, California mastitis test (CMT), rapid culture, portable/hand-held electrical conductivity meter, infrared thermography, leukocyte esterase strip test, milk pH, UdderCheck test) were analyzed on the basis of five selection criteria (the market availability of the test, the diagnostic accuracy of the test, the cost of the test, the cow-side use of the test, and the practicality of the test). The selection criteria were determined based on literature review and stakeholder input. The weighting of the criteria with the AHP was based on the pairwise comparison of the criteria by stakeholders. The criteria were weighted from 1 to 9 according to their relative importance as follows: “1: equally important,” “3: moderately important,” “5: strongly important,” “7: very strongly important,” “9: extremely important,” and “2, 4, 6, 8: intermediate values.” Final ranking of SCM tests with the TOPSIS was based on the stakeholder evaluations of fulfillment of the criteria by the alternatives. The most appropriate screening test for both large- and small-scale dairy farms was determined to be the CMT. The CMT is a very useful, easy to perform, and low-cost tool for detecting subclinical mastitis. Being a major element of udder health control programs, the CMT, if regularly used on dairy farms in Türkiye, would enable the culling of chronically infected animals and the reduction of mastitis-associated economic losses. Furthermore, regular CMTs would contribute to reducing milk SCC and improving milk quality. In conclusion, multi-criteria decision-making methods not only provide a systematic approach that may assist both veterinarians and farmers in deciding on the best choice among the different tests available for the screening of subclinical mastitis but also offer potential benefits to policymakers, researchers, and other industry stakeholders.

Candidiasis, caused by opportunistic fungal pathogens of the Candida genus, poses a significant threat to immunocompromised individuals. Natural compounds derived from medicinal plants have gained attention as potential sources of anti-fungal agents. Ajwa dates (Phoenix dactylifera L.) have been recognized for their diverse phytochemical composition and therapeutic potential. In this study, we employed a multi-faceted approach to explore the anti-candidiasis potential of Ajwa dates’ phytochemicals. Utilizing network pharmacology, we constructed an interaction network to elucidate the intricate relationships between Ajwa dates phytoconstituents and the Candida-associated molecular targets of humans. Our analysis revealed key nodes in the network (STAT3, IL-2, PTPRC, STAT1, CASP1, ALB, TP53, TLR4, TNF and PPARG), suggesting the potential modulation of several crucial processes (the regulation of the response to a cytokine stimulus, regulation of the inflammatory response, positive regulation of cytokine production, cellular response to external stimulus, etc.) and fungal pathways (Th17 cell differentiation, the Toll-like receptor signaling pathway, the C-type lectin receptor signaling pathway and necroptosis). To validate these findings, molecular docking studies were conducted, revealing the binding affinities of the phytochemicals towards selected Candida protein targets of humans (ALB–rutin (−9.7 kJ/mol), STAT1–rutin (−9.2 kJ/mol), STAT3–isoquercetin (−8.7 kJ/mol), IL2–β-carotene (−8.5 kJ/mol), CASP1–β-carotene (−8.2 kJ/mol), TP53–isoquercetin (−8.8 kJ/mol), PPARG–luteolin (−8.3 kJ/mol), TNF–βcarotene (−7.7 kJ/mol), TLR4–rutin (−7.4 kJ/mol) and PTPRC–rutin (−7.0 kJ/mol)). Furthermore, molecular dynamics simulations of rutin–ALB and rutin-STAT1 complex were performed to gain insights into the stability and dynamics of the identified ligand–target complexes over time. Overall, the results not only contribute to the understanding of the molecular interactions underlying the anti-fungal potential of specific phytochemicals of Ajwa dates in humans but also provide a rational basis for the development of novel therapeutic strategies against candidiasis in humans. This study underscores the significance of network pharmacology, molecular docking and dynamics simulations in accelerating the discovery of natural products as effective anti-fungal agents. However, further experimental validation of the identified compounds is warranted to translate these findings into practical therapeutic applications.

Drought is an important abiotic stress factor that severely affects plant growth, especially in arid and semi-arid regions. The effect of limited irrigation on plant growth and its response depending on growth stages is critical for agriculture in these regions. This study was conducted to understand how different pepper species ( C. annuum L. and C. chinense Jacq.) respond to drought conditions. Plants were subjected to four different irrigation regimes (100% field capacity (FC), 75% FC, 50% FC, and 25% FC) and three developmental stages (S1: 20 days after flowering, S2: 40 days after flowering, and S3: 60 days after flowering). The effects of drought on plant morphological growth, photosynthetic pigment content in leaves, phytochemical components [total phenolics (TPh), total flavonoids (TFv), and total antioxidant activity (TAa)], proline (PRL), protein (PRO), malondialdehyde (MDA), and activities of major antioxidant enzymes [catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD)] were investigated. According to the results, drought had a negative effect on plant morphology and physiology of both species, and these effects differed between plant species. The amounts of phytochemicals, MDA, PRO, PRL, and antioxidant enzymes increased in higher percentages with increasing drought severity (especially at S2 and S3 growth stages) in C. annuum . Moreover, antioxidative enzyme activities were significantly higher in C. annuum with increasing stress severity, helping the species to overcome oxidative stress under drought conditions. In conclusion, the findings showed that C. annuum is a drought-tolerant species with much more stable morphological, physiological, and biochemical performances compared to C. chinense .

The current age is typically referred to as the “Age of Uncertainty” because it is characterized by scholars due to rapid and multiple changes in different fields. The social, environmental, economic, political, and technological fields are the main subjects of these changes. However, our understanding and comprehension of these situations are restricted which brings failure in forecasts and projections for the subject. While certainty implies a clear knowledge of reality, doubt suggests a surreal grasp of reality. “The Age of Uncertainty” is driven by a range of complicated, interdependent, and ever-changing variables. According to some scholars, investment, macroeconomic and microeconomic factors, stock market volatility, and income inequality generate economic uncertainty. Environmental issues, particularly climate change, which threaten the future of humanity and the natural world are one of the contributing elements to “the age of uncertainty.” Climate change threatens infrastructure, biodiversity, economic stability, and human health. Extreme weather events, such as floods, heat waves, storms, and droughts, cause economic losses and infrastructural damage. Taking into account of the above-mentioned factors, triggering uncertainty, the chapter begins with a theoretical analysis of the Age of Uncertainty. The second part will analyse environmental uncertainty, focusing specifically on climate change and its impact on human migration. The third part examines the impact of the COVID-19 pandemic on climate-driven migration and the government’s reaction to this issue. The fourth part examines the problems that policymakers confront in addressing these issues. The fifth part will present strategies for enhancing resilience and modifying policymaking to face the problems of the age of uncertainty more effectively. The conclusion will argue that reinventing our relationship with uncertainty and change is essential for designing a fairer and more sustainable future.

In this study, the effects of the ripening process and fruit powder addition on the physical, chemical, total phenolic content, antioxidant capacity, volatile compounds, and sensory properties of Kashar cheese were determined. Total phenol content, antioxidant capacity, volatile compounds, and fatty acid esters were determined by Folin Ciocalteu, DPPH, SPME, and GC-MS, GC-FID, respectively. Of the 27 fatty acids identified in cheeses, palmitic, oleic, myristic, and stearic acids were found to have the highest ratios, respectively. While the total amount of phenol substance was 144.44 mg GAE/L in fresh, it increased to 374.84 mg GAE/L with ripening and 520.26 mg GAE/L with ripening + plant. A total of 58 volatile compounds, including 14 alcohols, 10 acids, 9 ketones, 9 hydrocarbons, 7 esters, 7 aldehydes,and 2 sulfur compounds, were detected in cheese. Alcohol (27.20%) in fresh kashar, acid (61.40%) in ripened kashar, and ketone (43.73%) in ripened + plant kashar were the volatile compounds groups determined at the highest rate. The ripening process and plant addition did not contribute positively to the sensory properties of the cheeses.

Molnupiravir (EIDD-2801) (MLN) is an oral antiviral drug for COVID-19 treatment, being integrated into viral RNA through RNA-dependent RNA polymerase (RdRp). Upon ingestion, MLN is transformed into two active metabolites: β-d-N4-hydroxycytidine (NHC) (EIDD-1931) in the host plasma, and EIDD-1931-triphosphate (MTP) within the host cells. However, recent studies provide increasing evidence of MLN’s interactions with off-target proteins beyond the viral genome, suggesting that the complete mechanisms of action of MLN remain unclear. The aim of this study was therefore to investigate the molecular interactions of MLN in the form of NHC and MTP with the non-RNA structural components of avian influenza (hemagglutinin, neuraminidase) and SARS-CoV-2 (spike glycoprotein, Mpro, and RdRp) viruses and to elucidate whether these two metabolites possess the ability to form stable complexes with these major viral components. Molecular docking of NHC and MTP was performed using AutoDock 4.2.6 and the obtained protein-drug complexes were submitted to 200-ns molecular dynamics simulations in triplicate with subsequent free energy calculations using GROMACS. Docking scores, molecular dynamics and MM/GBSA results showed that MTP was tightly bound within the active site of SARS-CoV-2 RdRp and remained highly stable throughout the 200-ns simulations. Besides, it was also shown that NHC and MTP formed moderately-to-highly stable molecular complexes with off-target receptors hemagglutinin, neuraminidase and Mpro, but rather weak interactions with spike glycoprotein. Our computational findings suggest that NHC and MTP may directly inhibit these receptors, and propose that additional studies on the off-target effects of MLN, i.e. real-time protein binding assays, should be performed.

There are many vague and uncertain issues in real-life. To address these problems, many models and theories have been developed. Entropy is used to express the mathematical values of the fuzziness of generalized hesitant trapezoidal fuzzy numbers (GHTF-numbers) and so it is a measure of the fuzziness of the GHTF-numbers. However, the entropy measures have not been applied to GHTF-numbers. Therefore, in the paper, we introduce the concept of entropy measures for GHTF-number and discuss its desirable properties. Then, we develop a VIKOR method based on the entropy measure for novel multi-criteria decision-making (MCDM) method. In the decision-making framework, the proposed method is not only a way to solve the problem of MCDM, but also contains an important mathematical idea as a different solution approach. We solve an illustrative example of the MCDM method and compare the obtained results with the results of other existing methods. The proposed VIKOR decision-making process is more suitable than the existing ones to deal with uncertain and imprecise information and offers numerous choices to the decision-maker for accessing the infinite alternatives. Furthermore, the result is more significant because the difference between any two values of alternatives is greater.

The aim of this study was to develop a valid and reliable measurement tool to measure teacher candidates’ perception of technological value orientations. Design/Methodology/ It was conducted based on data from 400 teacher candidates for explanatory factor analysis (EFA) and 680 teacher candidates for confirmatory factor analysis (CFA) in the 2018–2019 academic year. Expert opinions were sought for the content validity and face validity of the scale as well as the EFA and CFA were conducted for construct validity. EFA yielded a three-factor solution consisting of 12 items that accounted for 53.17% of total variance. These factors were labeled as “Negative Impact on Friendship, Honesty, and Responsibility”, “Negative Impact on Overall Values”, and “Positive Impact on Access to Information and Benevolence“. Cronbach’s Alpha internal consistency coefficient of the scale was found to be 0.75. Besides, findings from the CFA indicated that Technological Value Orientation Perception Scale of Teacher Candidates is of adequate fit with 12 items under a three-factor construct. In addition, the convergent and discriminant validity results also supported the three-factor structure. This scale could of help researchers to measure the perception of prospective teachers about the impact of technology on value-orientations and to plan desired studies accordingly.

This study aims to investigate the relationship between renewable energy and ecological footprint during the period of 1994–2018 from selected developing countries in Europe (Czechia, Croatia, Poland, Romania, Romania, and Turkey). In this context, the ecological footprint (EF), which has recently been the most widely used environmental indicator in the literature and is known as the most comprehensive because it includes many environmental factors, has been determined as the dependent variable. As independent variables, renewable energy consumption (REC), energy-related tax revenue (ETR), and energy productivity (EP) are included in the model. GDP and development of environment-related technologies (DET), which afect the ecological footprint in the model, are determined as control variables. As a result of the panel data analysis, according to the Durbin–Hausman cointegration test result, a long-term relationship between the variables was determined. According to the CCE estimator analysis, it can be said that there is a positive relationship between ETR and GDP variables and EF. For the AMG estimator analysis, it can be said that there is a positive relationship between GDP and EP variables and EF. Finally, according to the results of the Konya Causality test, a unidirectional causality relationship is detected from environmental technologies to the ecological footprint in Turkey, and a unidirectional causality relationship from the ecological footprint to GDP in Czechia, Romania, and Turkey. Furthermore, no causality relationship is detected between other variables. Based on the results, several policy implications are suggested.

The emergence of antibiotic resistance poses a serious threat to humankind, emphasizing the need for alternative antimicrobial agents. This study focuses on investigating the antibacterial, antibiofilm, and anti-quorum-sensing (anti-QS) activities of saponin-derived silver nanoparticles (AgNPs-S) obtained from Ajwa dates (Phoenix dactylifera L.). The design and synthesis of these novel nanoparticles were explored in the context of developing alternative strategies to combat bacterial infections. The Ajwa date saponin extract was used as a reducing and stabilizing agent to synthesize AgNPs-S, which was characterized using various analytical techniques, including UV–Vis spectroscopy, Fourier transform infrared (FTIR) spectroscopy, and transmission electron microscopy (TEM). The biosynthesized AgNPs-S exhibited potent antibacterial activity against both Gram-positive and Gram-negative bacteria due to their capability to disrupt bacterial cell membranes and the leakage of nucleic acid and protein contents. The AgNPs-S effectively inhibited biofilm formation and quorum-sensing (QS) activity by interfering with QS signaling molecules, which play a pivotal role in bacterial virulence and pathogenicity. Furthermore, the AgNPs-S demonstrated significant antioxidant activity against 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radicals and cytotoxicity against small lung cancer cells (A549 cells). Overall, the findings of the present study provide valuable insights into the potential use of these nanoparticles as alternative therapeutic agents for the design and development of novel antibiotics. Further investigations are warranted to elucidate the possible mechanism involved and safety concerns when it is used in vivo, paving the way for future therapeutic applications in combating bacterial infections and overcoming antibiotic resistance.

This study examined the relations between maternal education, children’s gender, writing readiness skills, and print awareness skills. Three hundred and sixteen 6-year-old children (183 girls and 133 boys) were assessed on writing readiness skills and print awareness skills. Spearman correlation coefficients were calculated to determine if there were significant relationships among maternal education, children’s gender, writing readiness skills, and print awareness skills. Also, a regression analysis was performed to measure the predictive strength of the variables on print awareness skills. The results showed that while the writing readiness skills were related to children’s print awareness skills; gender and maternal education were not correlated to print awareness skills. Regression analysis indicated that writing readiness skill is a predictor of print awareness skills. Writing readiness skills accounting for approximately 8% of the variance in print awareness skills. Findings are discussed in relation to the importance of understanding the connection between maternal education, children’s gender, writing readiness skills, and print awareness skills in supporting literacy development. These findings have important implications for practitioners as they work to involve determining the predictive power of writing skills and to support children in terms of these skills.

This study aims to investigate the relationship between renewable energy and ecological footprint during the period of 1994–2018 from selected developing countries in Europe (Czechia, Croatia, Poland, Romania, Romania, and Turkey). In this context, the ecological footprint (EF), which has recently been the most widely used environmental indicator in the literature and is known as the most comprehensive because it includes many environmental factors, has been determined as the dependent variable. As independent variables, renewable energy consumption (REC), energy-related tax revenue (ETR), and energy productivity (EP) are included in the model. GDP and development of environment-related technologies (DET), which affect the ecological footprint in the model, are determined as control variables. As a result of the panel data analysis, according to the Durbin–Hausman cointegration test result, a long-term relationship between the variables was determined. According to the CCE estimator analysis, it can be said that there is a positive relationship between ETR and GDP variables and EF. For the AMG estimator analysis, it can be said that there is a positive relationship between GDP and EP variables and EF. Finally, according to the results of the Konya Causality test, a unidirectional causality relationship is detected from environmental technologies to the ecological footprint in Turkey, and a unidirectional causality relationship from the ecological footprint to GDP in Czechia, Romania, and Turkey. Furthermore, no causality relationship is detected between other variables. Based on the results, several policy implications are suggested.

This study presents a novel method for accurately predicting the dynamic behavior of multistory frame buildings under earthquake ground motion. The proposed method allows approximately estimating the inter-story drift ratio, a crucial parameter strongly associated with building damage, its distribution along the building height, and its maximum value location. An equivalent continuous beam model with a rotation at the base, consisting of a combination of a shear beam and a flexural beam, is proposed to achieve this. This model derives closed-form solutions for the building’s dynamic characteristics. The lateral deformations along the height of frame buildings subjected to a given earthquake load, particularly the inter-story drift ratio profiles, and the maximum inter-story drift ratio parameter, are investigated. The proposed continuous model requires two dimensionless parameters: the lateral stiffness ratio (α) and the rotation at the base (θ), representing the drift ratio of the first story. For the expression of the lateral stiffness ratio (α) coefficient, a simple equation is also proposed using the beam-to-column stiffness ratio (ρ, or Blume coefficient) associated with the framed (discrete) system. Various building models are employed to validate the proposed method, demonstrating its applicability to both high-rise and low-rise building configurations. With the results obtained, it is shown that the proposed continuous model can be used not only for high-rise or multistory building models but also for low-rise building models.

The aim of this paper is the optimal scheduling of an active distribution network at the feeder scale to achieve minimum operating costs. To achieve this goal, a two-stage stochastic programming approach is presented that consists of here-and-now and wait-and-see decisions. In order to handle the uncertain parameters in the model, with the Monte Carlo simulation approach, different scenarios were produced, and then the scenarios were reduced. As a result, the mathematical problem is formulated as a linear model programmed in GAMS and then resolved with CPLEX solver. The effectiveness of the proposed model is assured through simulation studies on the standard IEEE 33-bus test system. The operating costs were calculated under different network conditions and were compared among themselves and according to the availability of storage. Obtained operating cost results have indicated that there is 6.4% cost reduction in the case where storage is used under the same conditions, compared to the case where no storage is used.

In this study, methanol, ethanol, dichloromethane:methanol (1:1, v/v), acetone, ethyl acetate, diethyl ether, and chloroform extracts of lavender (Lavandula stoechas L. subsp. stoechas) were prepared by maceration, and the ursolic acid contents in the extracts were determined quantitatively by HPLC analyses. The present results show that the methanol-dichloromethane (1:1, v/v) solvent system is the most efficient solvent system for the extraction of ursolic acid from the plant sample with the highest yield (2.22 g/100g plant sample). In the present study, a new practical method for the isolation of ursolic acid from polar extracts was also demonstrated for the first time. The inhibition effects of the extracts and ursolic acid were also revealed on α-glycosidase, acetylcholinesterase, butyrylcholinesterase, and human carbonic anhydrase I and II enzymes by determining IC50 values for the first time. The extracts and ursolic acid acted as potent antidiabetic agents by strongly inhibiting the α-glycosidase activity, whereas they were found to be very weak neuroprotective agents. In view of the present results, L. stoechas and its major metabolite, ursolic acid, can be recommended as a herbal source to control postprandial blood sugar levels and prevent diabetes by delaying the digestion of starch in food.

On the 30 th of October 2020, a 6.6 magnitude earthquake occurred 14 km north of Samos Island, causing 119 casualties (117 in Izmir, Tü rkiye, and 2 in Samos, Greece) and significant damage in the 3 rd biggest city of Tü rkiye, Izmir. Although the city is roughly 70 km far away from the epicenter, the damage was significant and concentrated in the city center settled on alluviums. This paper aims to analyze the distribution of damage in Izmir province, by crosschecking the recorded motions, the subsoil conditions and the evidence of damage as collected by an ad-hoc on-site reconnaissance. The intrinsic behavior of the Samos earthquake was investigated by employing three different ground-motion prediction equations. The results of the analyses revealed that site effects play a significant role in the amplification of ground motions, and valley effects are responsible for the concentration of damage. The damage in buildings was classified in terms of the intensity and structural typologies for the 30 districts of Izmir metropolitan area. In-depth analysis of the distribution of damages revealed that the earthquake caused damage all over the boundaries of Izmir province, and the concentration of damage in Bornova and Kars ßıyaka districts has a clear correlation with double resonance effects.

Excessive growth and abnormal use of dyes and water in the textile industry cause serious environmental problems, especially with excessive pollution of water bodies. Adsorption is an attractive, feasible, low-cost, highly efficient and sustainable technique in terms of green chemistry for the removal of pollutants from water. This study aims to investigate the removal kinetics, thermodynamics and adsorption mechanism of Remazol Red RB, which was chosen as a representative anionic reactive dye, from synthetic wastewater using powdered pumice, taking into account various experimental parameters such as initial dye concentration, adsorption time, temperature and pH. Moreover, to support the proposed adsorption mechanism, before and after adsorption of the samples, the Fourier transform infrared spectrophotometer (FTIR) spectra, X-ray powder diffraction (XRD) diffractograms and High resolution transmission electron microscopy (HRTEM) images were also taken and used. The results show that powder pumice can be an efficient adsorbent for anionic dye removal with a relatively high adsorption capacity of 38.90 mg/g, and it is very effective in 30–60 min in mild conditions. The experimental data showed a high agreement with the pseudo-second-order kinetic model and the Freundlich adsorption isotherm equation. In addition, thermodynamically, the process exhibited exothermic nature and standard isosteric enthalpy and entropy changes of −4.93 kJ/mol and 16.11 J/mol. K were calculated. It was determined that the adsorption mechanism was predominantly based on T-shaped pi-pi interactions and had physical characteristics.