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Plant stress detection is crucial for enhancing crop yield, particularly in the face of climate change. Cold stress significantly affects photosynthetic activity and pigment composition in soybean (a C3 plant) and maize (a C4 plant), underscoring the need to identify stress signals before irreversible damage occurs. This study used portable spectrometers to non-destructively detect the early signs of cold stress-related processes in these crops. The spectral reflectance indices were measured to identify crop-specific stress responses. According to the results, pigment-based indices have better potential for crop-specific stress detection than general stress response indices. The normalized phaeophytinization index (NPQI) and normalized pigment chlorophyll index (NPCI) exhibited diverse responses in C4 maize compared to C3 soybean, indicating the potential for discerning stress-induced changes in chlorophyll and other pigment contents. The photochemical reflectance index (PRI), modified to specific wavelengths, emerged as a crucial tool for stress detection in both crops, showing strong correlations with photosynthetic parameters and biomass traits. Specifically, the strongest correlation was found between PRI(525, 570) and fresh mass in maize and PRI(555, 570) and fresh mass in soybean. This approach underscores the importance of advanced spectral techniques in understanding and improving crop responses to cold stress, highlighting their potential for precision agriculture.

Abstract Robust object detection is crucial for automating underwater marine debris collection. While supervised deep learning achieves state-of-the-art performance in discriminative tasks, replicating this success on underwater data is challenging. The generalization of these methods suffers due to a lack of available annotated data considering different sources of variation in the unstructured underwater environment and imaging conditions. In this paper, we present the Seaclear Marine Debris Dataset, the first publicly available shallow-water marine debris dataset annotated for instance segmentation/object detection. The dataset contains 8610 images collected using ROVs at multiple locations and with different cameras, annotated for 40 object categories, encompassing not only litter but also observed animals, plants, and robot parts. As part of the technical validation, we provide baseline results for object detection using Faster RCNN and YOLOv6 models. Furthermore, we demonstrate the non-triviality of generalizing the trained model performance to unseen sites and cameras due to domain shift. This underscores the value of the presented dataset in further developing robust models for underwater debris detection.

Peroxidases are essential elements in many biotechnological applications. An especially interesting concept involves split enzymes, where the enzyme is separated into two smaller and inactive proteins that can dimerize into a fully active enzyme. Such split forms were developed for the horseradish peroxidase (HRP) and ascorbate peroxidase (APX) already. Both peroxidases have a high potential for biotechnology applications. In the present study, we performed biophysical comparisons of these two peroxidases and their split analogues. The active site availability is similar for all four structures. The split enzymes are comparable in stability with their native analogues, meaning that they can be used for further biotechnology applications. Also, the tertiary structures of the two peroxidases are similar. However, differences that might help in choosing one system over another for biotechnology applications were noticed. The main difference between the two systems is glycosylation which is not present in the case of APX/sAPEX2, while it has a high impact on the HRP/sHRP stability. Further differences are calcium ions and cysteine bridges that are present only in the case of HRP/sHRP. Finally, computational results identified sAPEX2 as the systems with the smallest structural variations during molecular dynamics simulations showing its dominant stability comparing to other simulated proteins. Taken all together, the sAPEX2 system has a high potential for biotechnological applications due to the lack of glycans and cysteines, as well as due to high stability.

The aim of this paper is to determine the interdependence between allocations to culture and the satisfaction of citizens with the programme content of theatres in the city of Rijeka, the 2020 European Capital of Culture. Of the ten hypotheses formulated in the paper, five are accepted and five, rejected. This study has applied several scientific methods, in particular the methods of descriptive and inferential statistics (correlation analysis, t-test, ANOVA). The principle finding of this paper indicates that the level of satisfaction of Rijeka's citizens with allocations to culture, sports and social activities and, consequently, with allocations to theatres, is low. The satisfaction of citizens with the theatres' programme contents is statistically more significantly determined by demographic variables than by satisfaction with allocations to culture, sport and social activities.

This research delves into the factors influencing the adoption of ChatGPT, a sophisticated AI-based chatbot, among Generation Z members in Croatia. Employing an extended UTAUT2 model, the impact of various factors on the behavioral intention to use ChatGPT is explored. The study included 694 Generation Z participants, and data were collected through an online survey featuring self-reporting questions. The analysis utilized statistical software packages for performing both confirmatory and exploratory factor analyses, in addition to hierarchical linear regression. Key findings reveal that performance expectancy, social influence, hedonic motivation, habit, and personal innovativeness significantly influence the behavioral intention to use ChatGPT. However, effort expectancy, facilitating conditions, and price value do not exhibit a significant impact. Notably, the study excludes the use behavior factor due to multicollinearity issues with behavioral intention. While the research does not focus on moderating factors, it reports that the adapted UTAUT2 model explains 65% of the variance in the adoption of ChatGPT by Generation Z users.

Abstract Background Autonomic nervous system (ANS) testing has aided in our ability to evaluate autonomic dysfunction in migraine patients. We reviewed the literature in multiple databases which investigate ANS function in migraine patients and healthy subjects. Methods This systematic review and meta-analysis examined the respective deep breathing, Valsalva manoeuvre, orthostatic and isometric challenge results, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analyses of Observational Studies in Epidemiology (MOOSE) statements. Results Seven articles met all inclusion criteria. Fixed-effects meta-analysis showed migraine patients (n = 424), collectively, had lower interictal autonomic test results compared with healthy controls (n = 268). In detail, this was true for the standardized mean difference (g) of deep breathing (g= -0.32; 95% confidence interval (CI) -0.48, -0.16), orthostatic challenge (g= -0.28; 95% CI -0.44, -0.13) and isometric challenge (g= -0.55; 95% CI -0.71, -0.39) and for the difference of means (MD) of the Valsalva ratio (MD = -0.17; 95% CI -0.23, -0.10). Conclusions Interictal ANS dysfunction can be identified in migraine patients when compared to healthy controls. These findings indicate the importance to evaluate ANS function in migraine patients - especially, as migraine-specific prophylactic therapies (such as anti-calcitonin gene-related peptide (CGRP) antibodies) may affect the function of the ANS.

The signing of the Paris Agreement represents a consensus on limiting the increase of the average global temperature compared to the preindustrial period. The European Union has set an ambitious goal of achieving climate neutrality by 2050. By 2030, the European Commission's REPowerEU plan aims to accelerate the processes of increasing the share of renewable energy sources, improving energy efficiency, reducing energy use, and, at the same time, diversifying energy sources and increasing electricity connectivity between member states.In order to achieve the stated goals, future energy systems will be based on renewable energy sources, which are characterized by production variability. Such systems require flexibilization technologies that ensure security and stability of supply. In this study, an analysis of how different fuel and technology costs, as well as policy targets, influence the pace of the energy transition dynamic was made on the case study of Croatia, as there was no such previous investigation. Therefore, the goal of the research is to identify the most prominent driver to achieve energy transition targets in Croatia, with an emphasis on the required flexibilization technologies. The investigation has been implemented in the energy planning tool H2RES, a detailed open-source long-term optimization model in a five-year step model based on scenario analysis of different RES and CO2 targets, technology costs, and fuel prices. The results reveal a need for an ambitious energy policy if the goal is to achieve full energy system decarbonization. Currently, high carbon prices and lower technology costs won't be enough to lead the energy transition, without legislative support.

Tetralogy of Fallot is the most common cyanotic congenital heart disease. This severe disorder of cardiac physiology can impair renal function and lead to the development of cardiorenal syndrome and eventually to end-stage renal disease. Kidney transplantation may be the best option for renal replacement treatment in patients with tetralogy of Fallot, but only after correcting cardiac abnormalities and optimizing cardiac functions, all of which require a multidisciplinary approach. We report the first case of kidney transplantation in an adolescent patient with tetralogy of Fallot. Our findings confirms that kidney transplantation is a valuable treatment option in selected congenital heart disease cases.

Calibration of low-cost humidity sensors such as the HTS221TR is critical for accurate measurements, especially in smart devices. This study compares two calibration methods: machine learning (PyTorchNeural Network regression model) and optimization algorithm with Engineering Equation Solver. The critical role of temperature in humidity measurement emphasizes that it must be included for a valid calibration. The machine learning approach significantly reduced the average deviation of humidity, reaching ±2,5% compared to the original ±13,4%. Additionally, it aligned mean values along the identity line. However, the performance of the model varied across the different humidity ranges. Applying the model to real-world scenarios showed that the model underestimates humidity, likely due to the sensor's inherent tendency to overestimate humidity, especially at higher temperatures. Despite these challenges, both calibration methods offer simple and effective approaches for correcting low-cost sensor measurements, with machine learning enabling faster processing. This study not only improves the accuracy of the HTS221TR sensor, but also paves the way for more accurate and affordable humidity measurement technologies in general.

The accuracy of guiding a spindle is greatly influenced by the thermal load of the bearing. Increased thermal load implies deformation of the bearing parts which is directly reflected in the work quality of the machine system. For this reason, the aim of this paper is to analyse the influence of the material and the geometry of the housing on the temperature field of the threaded spindle bearing assembly, which was realised by "radially mounting" of axial angular contact ball bearing ZKLN. This paper represents a new approach for thermal analysis of the special bearings, type ZKLN which are not involved in the relevant standards for the determination of the reference speed. At the same time the value of this paper finds itself in finding of the guideline at engineering practice which is very important at early design phase of the systems with threaded spindle. The analysis was carried out using experimental and numerical methods. Combination of the mentioned methods gave result which was used to define appropriate guideline regarding influence of housing material and geometry on thermal stability of the ZKLN bearing.

The effect of turmeric powder and a mix of turmeric powder and black pepper on the physicochemical properties of ice cream samples was examined. Enriched ice creams were manufactured by adding turmeric powder at levels of 0.5 %, 1.0 % and 2.0 %, with or without 0.02 % black pepper and compared with the control ice cream sample. Samples were analysed for proximate composition, pH value, water activity (aw), rheological properties, overrun, fat destabilization, hardness, melting properties, and colour parameters. The results of the study showed that the addition of spices significantly increased pH values (from 6.66 to 6.73), total solids (from 36.43 to 37.53 %), and carbohydrate contents (from 21.47 to 22.53 %) of the samples. Furthermore, this enrichment leads to an increase in the viscosity (from 0.44 to 0.70 Pa s) and thixotropic behaviours of ice cream mixes. Enriched ice creams had higher air incorporation, lower fat destabilization degree, and softer texture. In terms of melting properties, the melting resistance of ice cream samples was enhanced with the addition of spices. The colour properties of ice creams were significantly (p

This study aims to analyze and identify the strengths and interests of state actors and non-state actors in the revitalization of residents’ houses in the riverside area of Banjarmasin City from the perspective of Collaborative Governance. This study used a qualitative approach by collecting data through observation, in-depth analysis, and document analysis. The findings of this study explain that collaborative governance is an alternative to public policy as an interactive process involving state and non-state actors autonomously who use shared rules and norms carried out collectively to solve societal problems. Collaboration involving actors in power with interests in decision-making might fail during its implementation. This research contributes to the scientific literature on interactions between actors and collaborative governance because the problems faced by the public are fought for, and collaborative governance implementation cannot be separated from the presence of actors involved in advocating for issues of public concern.

In the 1980s, in parallel to the decline of large-scale planning, a local critique of modernist urbanism came to dominate the planning discourse in Zagreb, one that sought to implement strategies of urban regeneration on the omnipresent strata of persisting agricultural lots, and would soon be inscribed as the guiding ethos in the last socialist general plan. Concentrating their efforts on the central area of Trnje, then littered with scattered zones of informal construction that had hitherto resisted generation after generation of ambitious plans to convert it into a central representative and commercial part of Zagreb, local urban planners gradually formulated an innovative system of urban renewal that would enable its programmatic and morphological integration with the historic city. Breaking with the already exhausted expansionist strategy of large-scale greenfield planning, they strove to direct the future development of the city towards the densification and improvement of urban quality for previously “skipped-over” areas, with a newly found appreciation for the idiosyncrasies and complexities of the existing agricultural morphologies and heterogeneous buildings. The peculiar and deliberate choice of this kind of underlying urban strata as the basis of process-based urban renewal to harness the potential of both commercial and private actors promised a pronouncedly different urban outcome than the tabula rasa approach deployed at the apex of modernist urban planning only a decade earlier. However, the complex gestation process of required executive documents, the failure to create sufficient mechanisms of control, and the subsequent ascension of private ownership as the dominant spatial value all helped to usher in a period of frantic individual construction, signalling an abrupt end of this experiment. Rather than mere manifestations of capitalist transition, these processes will be framed as unintended echoes of the paradigm shift within the plans themselves.

Postupkom hladnog prešanja iz sjemenki lana i jezgre lješnjaka proizvodi se jestivo ulje visoke nutritivne vrijednosti. U ovom radu istraživan je utjecaj dodatka antioksidanasa (prirodni, sintetski) i sinergista na oksidacijsku stabilnost mješavine lješnjakovog i lanenog ulja (50:50). Od prirodnih antioksidanasa korišteni su ekstrakt kadulje, ekstrakt ružmarina, ekstrakt nara, mješavina tokoferola, eterično ulje konopljike, lavande, slatkog pelina, divlje mrkve, smilja, a od sintetskih propil galat. Određivanje oksidacijske stabilnosti mješavine ulja te utjecaj dodatka antioksidansa i sinergista provedeno je testom ubrzane oksidacije ulja Schaal Oven testom. Rezultat oksidacije mješavine ulja izražen je peroksidnim brojem. Primjenom standardnih metoda u ulju su određeni osnovni parametri kvalitete (peroksidni broj, slobodne masne kiseline, voda, netopljive nečistoće). Rezultati ispitivanja pokazuju da ekstrakt ružmarina (sa i bez limunske kiseline) efikasnije štiti mješavinu ulja od oksidacijskog kvarenja u odnosu na druge ispitivane antioksidanse. Eterično ulje slatkog pelina ne pokazuje utjecaj na stabilizaciju ove mješavine ulja.

The chemical and sensory properties of corn extrudates enriched with spray-dried tomato powder (TP) in 4, 6 and 8% ratios were researched. Two extrusion temperature regimes were used: 135/170/170 °C (E1) and 100/150/150 °C (E2). Ascorbic acid (AA) at levels of 0.5 and 1% was also added to the raw mixtures in order to prevent the undesirable oxidation of the constituents, primarily carotenoids. AA was especially efficient in the case of the lutein content and 1% AA, but lutein originating from TP was more sensitive to the extrusion conditions than corn lutein, and zeaxanthin was more sensitive than lutein. Lycopene, α-carotene, 13-cis-β carotene and 9-cis-β carotene degraded completely in all the samples, at both extrusion regimes. The proposed models for the color of the extrudates showed the significant influence of TP and AA. Extrudates obtained at the E1 temperature regime containing 4% TP and pure corn extrudate with 1% AA were the best-rated samples by the sensory panel.