Zeta potential emerges as a crucial parameter in understanding particle surface charges and assessing the stability of colloidal systems. It also serves as a key indicator in determining electrostatic interactions between surfaces and ions. In this study, hydroxyapatite (HA) derived from fish waste was functionalized with histidine (HA4) and 4-Aminohippuric acid (HA5), and their surface properties and heavy metal ion (Cu2+) adsorption capacities were investigated. Zeta potential measurements performed after surface modification showed that both modifications induced a negative charge on the surface. The surface modified with histidine exhibited a zeta potential in the range of -3.48 to -5.09 mV, while the surface modified with 4-Aminohippuric acid demonstrated a higher negative charge. Adsorption experiments revealed that HA5 exhibited a superior Cu2+ binding capacity of 9.96 mg/g compared to HA4 (9.52 mg/g). The findings indicate that zeta potential and the presence of functional groups on the surface play a significant role in the retention of heavy metal ions. These results suggest that modified fish bone surfaces can serve as effective and sustainable adsorbents for environmental applications.

This study presents the first comprehensive bibliometric analysis of research conducted between 1980 and 2025 on the invasive long-spined sea urchin Diadema setosum. Using VOSviewer, 213 publications retrieved from the Web of Science Core Collection (TS= “Diadema setosum”) were analyzed to assess publication trends, disciplinary scope, collaboration networks, citation impact, co-citation patterns and thematic clusters. The results reveal that the species is rapidly spreading in the Mediterranean and that there has been a sharp increase in publications since 2014, coinciding with a decline in 2022-2023 that corresponds to reported mass mortality events. The co-citation analysis consists of three intellectual clusters encompassing research on (i) marine ecology and echinoid phylogeography, (ii) invasion biology and Mediterranean monitoring, and (iii) disease ecology and mortality events. While marine and freshwater biology dominate the disciplinary profile, emerging environmental themes include ecotoxicology, microplastic exposure, pathogenic interactions, and biomaterial applications (e.g., chitin, chitosan, collagen), with low Total Link Strength (TLS) indicating limited integration. Japan, the USA and China are identified as the leading countries in research. Türkiye is placed within the top 10 in publication numbers but its citation visibility is reported as low because international collaboration is limited. An overall increase in publications has been observed after 2010 and studies related to the expansion of the species into the Mediterranean have contributed to this trend. Our findings indicate that research on D. setosum has traditionally been based on classical marine ecology and invasion frameworks, but is increasingly expanding into molecular ecology, disease dynamics and biotechnological applications. Supporting the sustainable use of the D. setosum species requires strengthening interdisciplinary approaches, encouraging multi-center collaborations, integrating open genomic and ecological data, understanding invasive dynamics, and assessing ecological risks.

Sea level rise, a critical consequence of global climate change, poses significant challenges to coastal communities worldwide. While long-term trends in sea level rise garner considerable attention, understanding and predicting interannual variability fluctuations are equally crucial for effective coastal management and adaptation. This research investigates detrended annual variability of adjusted sea level data, focusing on the unpredictable fluctuations superimposed on long-term trends. By employing Autoregressive Integrated Moving Average (ARIMA) modeling, this study aims to quantify and forecast these interannual variations, providing a statistical baseline that underscores the challenge of interannual variability prediction for coastal management. Utilizing adjusted annual sea level measurements from the National Oceanic and Atmospheric Administration (NOAA) spanning 1993 to 2019, this research isolates residual interannual fluctuations by removing the influence of long-term trends and other components through data adjustment. This adjustment process, typically incorporating corrections for factors like glacial isostatic adjustment (GIA) and vertical land motion (VLM), enables a focused analysis of the residual fluctuations. The adjusted sea level data was imported into the Minitab web platform for analysis. The “Forecast with Best ARIMA Model” tool within Minitab’s “Stat” menu was employed to automatically identify, fit and diagnose the most appropriate ARIMA model. This tool explores a range of potential ARIMA models, varying the order of autoregressive (AR), integrated (I) and moving average (MA) components, using the Akaike Information Criterion with correction (AICC) to select the best-fitting model while penalizing complexity. The results of this analysis reveal that, after an extensive screening of the ARIMA parameter space, the ARIMA(0,1,0) model, also known as the random walk with drift, emerged as the optimal representation of the adjusted sea level data. This suggests that the residual interannual variability, after accounting for factors removed during data adjustment, is largely unpredictable within the ARIMA framework. The selected model was then used to generate 100-year forecasts, from 2020 to 2119, along with 95% confidence intervals to quantify forecast uncertainty. The standard error of the forecasts was also analyzed, revealing a clear increase in uncertainty with longer forecast horizons. In conclusion, this research demonstrates that while the adjusted sea level exhibits significant annual variability, this variability is largely unpredictable using ARIMA models. This finding underscores the importance of separating the analysis of these kinds of fluctuations from the long-term sea level rise trend, which must be modeled using different approaches. The 100-year forecasts and associated confidence intervals provide valuable information for coastal communities to better prepare for and manage the risks associated with interannual sea level fluctuations, even if precise predictions are not possible. Concurrence of AICC, AIC and BIC provide strong support for validity of the model, reinforces the principle of parsimony, suggests genuine random walk behavior in the adjusted sea level data and increases confidence in the interpretation of the results. While the ARIMA(0,1,0) serves as a robust baseline for understanding the inherent unpredictability of adjusted sea level variations, future research could explore the potential of incorporating predictors, such as climate indices or employing non-linear time series models to further refine understanding and predictive capabilities concerning interannual sea level changes.

This study comparatively evaluates three nonlinear regression models (Richards, Gompertz, and Logistic) commonly used to mathematically model the growth process of commercial broilers. The primary objective of the study was to determine the model that most accurately represents the growth curve by analyzing the fit of these models to live weight data. In the study, 360 Ross 308 hybrid male broiler chicks were monitored until 50 days of age, and weekly live weight measurements were taken. Parameter estimates for each model were evaluated based on statistical fit metrics, including root mean square error (RMSE), coefficient of determination (R2), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). The results showed that the Richards model showed the highest fit across all criteria. The Gompertz model ranked second, and the Logistic model ranked third. However, all three models demonstrated high performance in explaining the growth process of broilers. These results highlight the importance of growth modeling as a key decision-support tool for determining optimal slaughter timing and feeding strategies, particularly in broiler production. The flexible structure of the Richards model makes it the most desirable option in terms of biological significance and statistical relevance.

This paper explores how wheat import volumes in Intergovernmental Authority on Development (IGAD) countries respond to global price changes, and whether these reactions vary across countries or over time. Wheat is a critical staple in the region, and its import dynamics are increasingly important as the bloc faces recurring shocks like drought, conflict, and global price spikes. Using a two-pronged approach, we first apply country-level autoregressive distributed lag (ARDL) models and find long-run cointegration across all IGAD members. Eritrea and Ethiopia show strong long-run negative price elasticities, pointing to substitution or price-sensitive behavior. South Sudan, Sudan, and Somalia display short-run positive responses, likely linked to urgent procurement or aid-related deliveries. Uganda shows limited responsiveness, while Djibouti—though also reactive in the short term—likely reflects its role as a re-export hub rather than fragility-driven volatility. Kenya shows both long-run sensitivity and short-run spikes, indicating a more complex market and policy mix. At the bloc level, panel Granger causality tests reveal a two-way relationship between global wheat prices and imports. Notably, imports also Granger-cause price shifts—an unexpected result suggesting that even uncoordinated regional import behavior may shape market expectations. This finding strengthens the case for more strategic procurement and regional storage mechanisms.

Abandoned, lost, or otherwise discarded fishing gear (ALDFG) poses a persistent threat to marine biodiversity and fisheries economies. İskenderun Bay in the Northeastern Mediterranean Sea, an ecologically productive and fishing-intensive region, has been increasingly affected by ghost fishing caused by ALDFG. This study aimed to (1) assess the ecological and economic impacts of ghost fishing, (2) document and retrieve ALDFG using minimally invasive methods, and (3) evaluate the cost-effectiveness of gear removal operations. Between May 2014 and April 2015, ghost nets were located and retrieved in İskenderun Bay using a combination of fishers’ interviews, SCUBA, ROVs, and surface-supplied diving. Three key sites were selected for retrieval operations using a balloon lifting method. Seabed types were categorized into four habitat classes based on depth and substrate composition. In total, 565 kg of derelict fishing gear, including purse-seine and trammel nets, was successfully recovered from the survey area. Reusable and recyclable materials amounted to $5,097.72 in theoretical income, resulting in a net economic loss of $18,510. Elongation nets, especially those lost in rocky coastal areas, posed the highest environmental risk due to their persistent ghost fishing activity. This study represents the first large-scale ALDFG retrieval and economic assessment in the Northeastern Mediterranean Sea. The findings emphasize the need for systematic ALDFG monitoring, biodegradable gear use, and community-based education. Balloon-assisted lifting proved to be an effective and ecologically responsible retrieval technique. Establishing reporting mechanisms and policy frameworks is vital for mitigating ghost fishing impacts in Türkiye and similar coastal regions.

Due to the increasing importance of using environmentally friendly methods to increase the yield of crops, two- year experiment carried out in a field located in the Dehgolan region, in the northwest of Iran, to study influence of sulfur spraying and plant growth promoting rhizobacteria inoculation on canola traits. The experiment was arranged as a split-plot factorial arrangement based on randomized complete block design with three replications. The main plots included two levels of sulfur (control and application), and the factorial combinations of strigolactone (control and application) and microorganisms (control, Funneliformis mosseae, Bacillus lentus, Pseudomonas fluorescens, Thiobacillus sp.) were allocated to the sub-plots. The results of combined analysis showed that the 1000 seed weights and seed yield increased significantly by sulfur application. At the same time, the 1000 seed weights decreased under the influence of strigolactone. Also, the SPAD number, the number of pods and seeds per plant, the 1000 seed weights and the seed yield increased significantly by influence of microorganisms, especially Thiobacillus, compared to control treatment. Based on the results of interaction effects, all traits except the number of SPAD were affected by the interaction effect of sulfur, strigolactone and microorganisms. The application of sulfur along with strigolactone and Thiobacillus significantly increased the number of pods per plant (200), the 1000 seed weights (4.53 g) and the seed yield (2552 kg/ha).

Adaptogens, a class of natural substances derived primarily from plants, have gained significant attention for their potential to enhance human health and performance. These compounds are believed to help the body adapt to stress, improve cognitive function, boost immunomodulation and promote overall well-being. This review article is aimed to discuss the diverse world of adaptogens, exploring their historical use, mechanisms of action and scientific evidence supporting their efficacy. A range of adaptogens will be examined and discussed, including well-known examples like Withania somnifera (Ashwagandha), Rhodiola rosea and Panax ginseng, as well as lesser known but promising candidates. The highlights of the key potential benefits of adaptogens in various health conditions, such as anxiety, depression, fatigue and cognitive decline will be addressed. Additionally, the critical evaluation of the available scientific evidence will be mentioned, highlighting the need for rigorous clinical trials to further validate the claims surrounding adaptogens. By synthesizing information from diverse references, including traditional medicine, modern pharmacology and clinical research, this review aims to provide a comprehensive understanding of adaptogens and their potential applications in promoting human health and performance.

Bu çalışma, kimyasal, biyolojik, radyolojik ve nükleer (KBRN) eğitimlerinde ortaya çıkan insan hatalarının nedenlerini çok katmanlı bir sistem yaklaşımıyla incelemekte ve bu hataların eğitimsel süreçlere entegrasyonunu sağlayan bütünleşik bir değerlendirme modeli önermektedir. Çalışma aynı zamanda KBRN eğitimlerinde sıkça karşılaşılan ekipman kullanım hatalarının yalnızca teknik eksikliklerden değil, bilişsel yük, ergonomik kısıtlar, çevresel faktörler ve karar verme süreçlerindeki karmaşadan kaynaklandığını ortaya koymaktadır. Bununla birlikte, insan faktörleri kuramlarını, ergonomik analiz yaklaşımlarını ve operasyonel risk yönetimi ilkelerini birleştirerek hataların kök nedenlerini açıklamaya odaklanmıştır. Kuramsal çerçeve çok katmanlı bariyer mantığına dayanan Swiss Cheese modeli, hata sınıflandırma sistematiği sunan HFACS ve insan–ekipman–çevre etkileşimini irdeleyen SHELL modelinin sentezine dayanmaktadır. Bu üç modelin bütüncül olarak uygulanması, KBRN eğitimlerinde güvenlik kültürünün geliştirilmesine, senaryo temelli öğrenme yöntemlerinin etkinliğinin artırılmasına ve kişisel koruyucu ekipman kullanımında ergonomik optimizasyonun sağlanmasına katkı sunmaktadır. Çalışma insan hatası kuramlarını KBRN eğitimleri bağlamına uyarlayan disiplinler arası bir entegrasyon modeli önermesiyle diğer çalışmalardan öne çıkmaktadır. Elde edilen sonuçlar, model temelli eğitim tasarımının karar destek araçları ve standardize edilmiş iş akışlarıyla bütünleştirildiğinde operasyonel güvenliğin ölçülebilir biçimde güçlendiğini göstermektedir.