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Valorization black carrot colorant process liquid waste by clarification and Decolorization: A novel sugar alternative for gummies
No full textThe aim of this study was to develop a recycling process for black carrot colorant liquid waste (BCLW) and to investigate the potential use of BCLW as a sugar source for glucose syrup substitution in gummy candy production. Clarification and decolorization were performed using ion exchange and adsorbent resins at three flow rates, followed by evaporation. The highest clarity (88.7 %) was achieved with modified styrene-divinylbenzene resin at 1.0 BV/h. Subsequently, BCLW was incorporated into gummy formulations as a glucose syrup substitute. Higher hardness values were recorded in formulations with over 75 % of BCLW incorporated, compared to the gummy samples produced with 100 % glucose syrup. The brightness remained considerably high when the glucose syrup was replaced with BCLW up to 50 %. Accelerated shelf-life tests showed changes in color and hardness. BCLW presents a sustainable alternative for the confectionery industry, offering a practical solution for waste reduction while contributing to resource efficiency
İktidar, Neoliberalizm ve Yükseköğretim Yönetimi
No full textYirmi birinci yüzyılda yükseköğretim yönetimine ilişkin çözümleme yapabilmek adına güç ilişkilerini iktidar zemininde ele almak ve neoliberalizm ekseninde iktidarın kurumlarda ve özellikle insan hayatında nüfuz etme biçimlerini tartışmak önem arz etmektedir. Özellikle bilgi toplumu, post- modernist veya neoliberal gibi betimlemelerle çeşitli yönlerinin vurgulandığı mevcut toplumda, üniversitelerdeki pratikler de toplumsal dinamiklerden ve iktidarın işleme biçimlerinden etkilenmektedir. Dolayısıyla, değişen toplumsal ilişkilenme biçimlerini ve iktidar ilişkilerini irdelemenin yükseköğretim kurumlarındaki yönetim pratiklerini çözümlemek için kritik öneme sahip olduğu düşünülmektedir. Buradan hareketle, bu çalışmada, özellikle yükseköğretim kurumlarında iktidarın nasıl işlediğini ve bireylerin ve toplumların ekonomi politikaları ve yaşam politikalarıyla ilişkili olarak nasıl düzenlendiğini ve yönetildiğini çözümleyebilmek amacıyla özellikle biyopolitik iktidar ve neoliberal yönetimsellik kavramlarının incelenmesi ve bu konuda yükseköğretimde yapılan çalışmalar için temel bir bakış açısı sunulması amaçlanmıştır. Bu bağlamda, gerçekleşen politika değişikliklerine ve neoliberal yansımaların akademik kimliğe yansımalarına da değinilmiştir. Kısaca, bu araştırmada, konunun teorik temelleri verilerek literatüre dair kapsamlı bir analiz ortaya konmaya çalışılmıştır.It is essential to address power relations on the grounds of power and to discuss how power penetrates institutions, especially human life, in the context of neoliberalism to analyze higher education administration in the twenty-first century. In the current society, where various aspects are emphasized with descriptions such as information society, post-modernist, or neoliberal, practices in universities are also affected by social dynamics and how power operates. Therefore, examining changing forms of social and power relations is critically important to analyze administrative practices in higher education institutions. Based on this, this study aims to examine the concepts of biopolitical power and neoliberal governmentality in particular to explore how power operates in higher education institutions and how individuals and societies are organized and governed concerning economic policies and life policies, and to provide a fundamental perspective for studies conducted in higher education on this subject. This research attempted to present a comprehensive analysis of the literature by giving the theoretical foundations of the subject. In this context, the policy changes that took place and the reflections of neoliberalism on academic identity were also mentioned. This study aimed to thoroughly examine the literature by providing the theoretical underpinnings of the topic
A Robust Adaptive Nonlinear Controller for a MEMS Gyroscope with Position Dependent Error
No full textFunctional Properties of Postbiotics Derived From Liquorilactobacillus hordei SK-6 for Bio-Decontamination in Ready-To-Eat Lettuce
No full textThis study characterized the postbiotics produced by Lactiplantibacillus plantarum Y48, Liquorilactobacillus hordei SK-6, and Lp. plantarum VB-29, focusing on their antibacterial properties against Escherichia coli and Listeria monocytogenes in contaminated ready-to-eat lettuce. Postbiotic activity was evaluated using the disk diffusion method, minimum inhibitory concentration (MIC, mg/mL), minimum bactericidal concentration (MBC, mg/mL), antioxidant properties, and total phenolic content (TPC). The survival of pathogenic microorganisms in the presence of postbiotics was analyzed using the Baranyi model. The antioxidant content of the postbiotics ranged from 465 to 597 mg TE/100 g, while TPC values were between 1195 and 1353 mg GAE/100 g. Notably, Lq. hordei SK-6 postbiotics exhibited significant antibacterial activity, forming inhibition zones of 17 and 25 mm against E. coli and L. monocytogenes respectively, with a MIC value of 12.5 mg/mL for both pathogens. Based on these findings, Lq. hordei SK-6 postbiotics were tested in contaminated lettuce samples stored at 4 degrees C. The 3% postbiotic treatment reduced the E. coli population from 6.08 to 5.43 log10 CFU/g on Day 0, representing a statistically significant decrease (p < 0.05). After 48 h, the 1% postbiotic treatment reduced E. coli and L. monocytogenes by 0.59 and 0.82 log10 CFU/g, respectively, while a 3% postbiotic resulted in a 1.62 log10 CFU/g reduction in L. monocytogenes (p < 0.05). In conclusion, Lq. hordei SK-6 postbiotics demonstrated potential as a natural biodecontaminant tool to preserve and improve the microbial safety of ready-to-eat lettuce
Comparative Assessment of LiDAR Point Clouds Captured Using Inertial Labs RESEPI Gen-I-M2X and DJI Zenmuse L2 Sensors on UAS Platforms for Varying Terrain Conditions
No full textUnmanned Aerial Systems (UAS) equipped with LiDAR sensors are increasingly used for topographic surveying and mapping due to their ability to generate high-quality point clouds and penetrate vegetation. While photogrammetry remains a common approach in UAS mapping, its limitations in vegetated environments—where it often struggles to accurately capture ground surface details—have led to the adoption of LiDAR. LiDAR, with its capability to penetrate vegetation, provides more precise terrain observations and detailed representations of the underlying ground surface, even in densely vegetated areas. This study compares the performance of two LiDAR systems: the RESEPI Gen-I-M2X sensor from Inertial Labs, mounted on a WingtraOne Gen II fixed-wing UAS using post-processed kinematic (PPK) corrections; and the Zenmuse L2 sensor integrated with the DJI Matrice 350 RTK, utilizing real-time kinematic (RTK) corrections with additional PPK adjustments based on observation files from a local Continuously Operating Reference Station (CORS) acting as the base. Both platforms were flown over the same area, with point clouds analyzed across three distinct conditions: open terrain, urban development, and wooded areas. A total of 135 GNSS-measured reference points were deployed, with 10 designated as ground control points (GCPs) to enhance vertical accuracy, while the remaining 125 points served as checkpoints for validation. Some checkpoints were located at the center of manhole covers, others at painted arrow markers on roadways, but the majority—especially those in wooded areas—were natural points without signalization. The Zenmuse L2 datasets were processed in DJI Terra, generating point clouds with and without GCP integration. In contrast, the RESEPI Gen-I-M2X datasets relied solely on PPK corrections, as the processing software does not support GCP integration. This study evaluates the accuracy and noise levels of the point clouds in varying environments, focusing on terrain representation by the LiDAR sensors. The findings provide insights into the strengths and limitations of each platform and correction strategy, offering guidance for selecting appropriate UAS LiDAR systems for specific surveying and mapping applications. This research contributes to the growing body of work on UAS LiDAR by highlighting key factors that influence data quality, including sensor selection, correction methods, and environmental conditions
Search for excited tau leptons in the ττγ final state in proton-proton collisions at = 13 TeV
No full textResults are presented for a test of the compositeness of the heaviest charged lepton, τ, using data collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 13 TeV at the CERN LHC. The data were collected in 2016–2018 and correspond to an integrated luminosity of 138 fb−1. This analysis searches for tau lepton pair production in which one of the tau leptons is produced in an excited state and decays to a ground state tau lepton and a photon. The event selection consists of two isolated tau lepton decay candidates and a high-energy photon. The mass of the excited tau lepton is reconstructed using the missing transverse momentum in the event, assuming the momentum of the neutrinos from each tau lepton decay are aligned with the visible decay products. No excess of events above the standard model background prediction is observed. This null result is used to set lower bounds on the excited tau lepton mass. For a compositeness scale Λ equal to the excited tau lepton mass, excited tau leptons with masses below 4700 GeV are excluded at 95% confidence level; for Λ = 10 TeV this exclusion is set at 2800 GeV. This is the first experimental result covering this production and decay process in the excited tau mass range above 175 GeV
Leveraging renewable energy for Türkiye's future hydrogen supply chain
No full textAs energy and climate crises necessitate a shift to sustainable resources, hydrogen - with its zero-emission potential-is expected to play a key role in the energy transition. Designing an effective hydrogen supply chain (HSC) is essential to realizing this potential. This study introduces a multi-period, multi-objective stochastic optimization model for Türkiye's transportation-sector HSC. It addresses gaps in existing research by integrating dynamic renewable energy availability, lifecycle-based CO2 emissions, and regional green hydrogen prioritization. The ε-constraint method is used to balance economic and environmental objectives. Results show that Türkiye can significantly reduce emissions by gradually transitioning from fossil-based production and by optimizing facility locations based on regional solar, wind, and hydrogen sulfide potential. Centralized production reduces costs but increases transport risk and emissions, while localized production improves resilience yet may increase fossil fuel reliance in resource-limited regions. These findings offer strategic guidance for aligning hydrogen planning with Türkiye's climate commitments
Analyzing Cultural Erasure and Colonized Voices in Wilkie Collins's The Moonstone
No full textThe Moonstone, published in 1868, is a work of Victorian literature that has received little attention but is profoundly important. It sheds a definitive light on colonialism and the theme of othering set in the backdrop of a detective story. This paper discusses and attempts to unravel how the novel engages with the theme of British imperialism and the associated cultural considerations in its simplest form: a diamond is stolen from an Indian temple and brought to England. The Moonstone is a physical item, but its meaning expands to the symbol of the cultural and spiritual plundering requisite for colonial conquest. It prompts thinking around the notions of loss and belonging and the consequences of having imperial power. The novel's multi-narrative approach has been cited as a way of understanding how differing views on the same topic, in this case, colonialism and othering, can be affected by class and race. This argument is significant for understanding the different responses by British people to the curse of the diamond and the muted responses from Indian priests who wanted the diamond back. The article covers the erasure of the voices of the British-colonized Indian subjects and the moral dilemmas posed by the treasure mentioned above. It pursues the very goals Collins was critiquing by restating the divide between the rational West and the mystical East and how they embellish colonial rule. With a postcolonial view, this article explores the themes of guilt, cultural restoration, and displacement embedded in the text.</p
Deep Learning Based Sign Language Recognition Using Efficient Multi-Feature Attention Mechanism
No full textSign language is a communication system used by hearing-impaired people and serves as a bridge between hearing and deaf community. Since sign language uses numerous visuomotor elements that include both visual perception (hand shapes, facial expressions) and physical movements (hand and arm movements), it represents a multimodal input source for Sign Language Recognition (SLR) systems. In this study, a new deep learning-based architecture using EfficientNet and multi-feature attention mechanism is proposed to accurately recognize SL gestures. Initially, general visual features are acquired through the EfficientNet model, leveraging the transfer learning paradigm. Subsequently, dataset-specific contextual features are extracted utilizing distinct network types; spatial dependencies are modeled via Convolutional Neural Networks (CNNs), while temporal dynamics are learned through Recurrent Neural Networks (RNNs). These features are adaptively weighted using attention mechanism and focus on the most critical information for the classification task. This approach ensures that the most information-rich and useful components of both methods are emphasized, leading to a significant increase in final success performance. Utilizing RGB video images, the proposed model, on the BosphorusSign22k General dataset comprising Turkish Sign Language (TSL) words, achieved accuracies of 99.21% and 96.84% for word classes of 50 and 174, respectively. Furthermore, the generalization ability of the model is proven by its high accuracy of 99.94% in the Argentinian Sign Language dataset (LSA64) and 98.41% in the Indian Sign Language dataset (INCLUDE50). Experimental results indicate that the proposed model architecture has a competitive performance compared to existing SLR models reviewed in the literature
