U članku se analizira lokalna politika u općini Vukovar od pluralizacije po-litičkog života u Hrvatskoj početkom 1990. do sloma demokratski izabranih lokalnih političkih institucija u svibnju 1991. ...To razmjerno kratko razdoblje obilježila je snažna politička polarizacija između dviju najbrojnijih nacionalnih zajednica, Hrvata i Srba, u općini. U tom su procesu tri političke stranke – savez komunista Hrvatske-stranka demokratskih promjena, Hrvatska demokratska zajednica i Srpska demokratska stranka – bile glavni akteri nacionalne mobilizacije i političkog života u Vukovaru.
This article provides an analysis of local politics in the Vukovar municipality, from the pluralization of the political party scene in Croatia that started in early 1990 to the breakdown of democratically elected local institutions in may 1991. This relatively short period was marked by strong political polarization of the two largest national communities in the municipality, the Croats and the Serbs. In the process, there were three parties that played key roles in the political arena and in national mobilization – the League of Communists of Croatia/the Party of Democratic Change (sKH/sdP), the Croatian Democratic Union (Hdz) and the Serb Democratic Party (sds).
This study focuses on predicting and optimizing the quality parameters of cookies enriched with dehydrated peach through the application of Support Vector Machine (SVM) and Artificial Neural Network ...(ANN) models. The purpose of the study is to employ advanced machine learning techniques to understand the intricate relationships between input parameters, such as the presence of dehydrated peach and treatment methods (lyophilization and lyophilization with osmotic pretreatment), and output variables representing various quality aspects of cookies. For each of the 32 outputs, including the parameters of the basic chemical compositions of the cookie samples, selected mineral contents, moisture contents, baking characteristics, color properties, sensorial attributes, and antioxidant properties, separate models were constructed using SVMs and ANNs. Results showcase the efficiency of ANN models in predicting a diverse set of quality parameters with r
up to 1.000, with SVM models exhibiting slightly higher coefficients of determination for specific variables with r
reaching 0.981. The sensitivity analysis underscores the pivotal role of dehydrated peach and the positive influence of osmotic pretreatment on specific compositional attributes. Utilizing established Artificial Neural Network models, multi-objective optimization was conducted, revealing optimal formulation and factor values in cookie quality optimization. The optimal quantity of lyophilized peach with osmotic pretreatment for the cookie formulation was identified as 15%.
Osmotic drying of celery leaves was studied in two osmotic solutions (ternary aqueous solution and sugar beet molasses), at three temperatures (20, 35, and 50?C), and diverse immersion periods (1, 3, ...and 5 hours). The aim was to examine the influence of the used hypertonic agent, temperature and immersion time on antioxidant capacity (AOC) and color characteristics of the samples. The AOC of celery leaves was assessed by the spectrophotometric assays (ABTS, FRAP, and DPPH), as well as two direct current polarographic assays, hydroxo perhydroxo mercury (II) complex assay based on the decrease of anodic current of hydroxo perhydroxo mercury (II) complex and mercury reduction antioxidant power assay based on the decrease of a cathodic current of Hg (II) reduction. Total phenolic content was determined by Folin-Ciocalteu assay. The relative antioxidant capacity index, calculated by assigning equal weight to all applied assays was used to achieve a more comprehensive comparison between analyzed samples, as well as applied assays.The obtained results indicated decreases in the AOC of celery leaves during the osmotic treatment in ternary solution, while the AOC was increased in sugar beet molasses solution. According to relative antioxidant capacity index evaluation the most convenient process parameters were temperature of 35 ?C and immersion time of 5 hours.
Being able to infer the clonal evolution and progression of cancer makes it possible to devise targeted therapies to treat the disease. As discussed in several studies, understanding the history of ...accumulation and the evolution of mutations during cancer progression is of key importance when devising treatment strategies. Given the importance of the task, many methods for phylogeny reconstructions have been developed over the years, mostly employing probabilistic frameworks. Our goal was to explore different methods to take on this phylogeny inference problem; therefore, we devised and implemented three different metaheuristic approaches—Particle Swarm Optimization (PSO), Genetic Programming (GP) and Variable Neighbourhood Search (VNS)—under the Perfect Phylogeny and the Dollo-k evolutionary models. We adapted the algorithms to be applied to this specific context, specifically to a tree-based search space, and proposed six different experimental settings, in increasing order of difficulty, to test the novel methods amongst themselves and against a state-of-the-art method. Of the three, the PSO shows particularly promising results and is comparable to published tools, even at this exploratory stage. Thus, we foresee great improvements if alternative definitions of distance and velocity in a tree space, capable of better handling such non-Euclidean search spaces, are devised in future works.
The article analyzes the situation in the footwear factory Borovo in the times of democratic changes in 1990. At the end of the 1980s the factory found itself in a serious crisis, mostly due to ...structural problems. Furthermore, strikes and conflicts of different levels of authority for custody over the factory were very frequent. First multiparty elections brought completely new political circumstances in the factory environment. However, in the factory there was still the same management as in the old system. In the article we examine, based on the example of the so-called June-strike of workers in 1990, to what extent the same socialist practice was still actual, that is, how the workers were offered a new framework of collective illusion, instead of making them face real problems. At the same time, the hard position of workers in Borovo was a “fertile ground” for nationalistic ideas. Based on the mentioned examples, we analyze the thesis about coalitio n of socialist elites and the working class by means of buying social peace. Furthermore, we analyze the thesis about nationalism as a new “collective mantle” which substitutes socialism. Finally, we examine to what extent democratic changes were truly a process of democratization rather than efforts of new actors to take over the position in society that was held by the Communist Party in the previous period.
This study explores the unexploited potential of Artificial Neural Network (ANN) optimization techniques in enhancing different drying methods and their influence on the characteristics of various ...sweet potato varieties. Focusing on the intricate interplay between drying methods and the unique characteristics of white, pink, orange, and purple sweet potatoes, the presented experimental study indicates the impact of ANN-driven optimization on food-related characteristics such as color, phenols content, biological activities (antioxidant, antimicrobial, anti-hyperglycemic, and anti-inflammatory), chemical, and mineral contents. The results unveil significant variations in drying method efficacy across different sweet potato types, underscoring the need for tailored optimization strategies. Specifically, purple sweet potatoes emerge as robust carriers of phenolic compounds, showcasing superior antioxidant activities. Furthermore, this study reveals the optimized parameters of dried sweet potato, such as total phenols content of 1677.76 mg/100 g and anti-inflammatory activity of 8.93%, anti-hyperglycemic activity of 24.42%. The upgraded antioxidant capability is presented through DPPH
, ABTS
, RP, and SoA assays with values of 1500.56, 10,083.37, 3130.81, and 22,753.97 μg TE/100 g, respectively. Additionally, the moisture content in the lyophilized sample reached a minimum of 2.97%, holding favorable chemical and mineral contents. The utilization of ANN optimization proves instrumental in interpreting complex interactions and unlocking efficiencies in sweet potato drying processes, thereby contributing valuable insights to food science and technology.
In this research series, several sugar beet molasses of different osmolalities were inoculated with a mix of the following microorganisms, Escherichia coli, Salmonella spp. and Listeria ...monocytogenes, to develop mathematical models and correlations of the effect of different levels of osmolality and different exposure time to the viability of the selected microorganisms. The respective enumerations of Escherichia coli, Salmonella spp., Listeria monocytogenes, Enterobacteriaceae, and total plate count were conducted on inoculated molasses samples of different osmolalities (from 5500 to 7000 mmol/kg) and at different exposure times (from 0 to 5 h). The results showed that by increasing molasses osmolalities, all the selected microorganisms’ exposure time viability measures statistically decreased significantly. Salmonella spp. showed the highest viability of all the tested microorganisms in a high osmotic environment. In contrast, Listeria monocytogenes showed the least resilience to osmotic stress, with a reduction in the numbers below the detection limit. The developed mathematical models of microorganisms’ viability exposed to molasses’s high-osmolality environment were statistically significant, allowing for the good prediction of a number of microorganisms based on exposure time and osmolality levels. The obtained results describe molasses’s excellent microbial load-reducing capability and provide the potential for applications in the production of safe foods.
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