1. Harnessing environmental yeasts - Pichia kudriavzevii strain ZMUM_K002 : the quest for isolates with properties for efficient biotechnological applicationsTadeja Vajdič, Marjanca Starčič Erjavec, 2025, original scientific article Abstract: The environment hosts a diversity of microorganisms whose potential for biotechnological applications has not yet been exhausted. The quest of our study was to find isolates of Pichia kudriavzevii from the environment that could be used as new biotechnological agents. Moreover, we aimed to explore the resource efficiency for microbial cultivation, in particular the efficiency of spent coffee grounds (SCG), an easily accessible waste coffee product with a high unutilized organic content. In this study, Pichia kudriavzevii strain ZMUM_K002, a yeast strain isolated from a grape pomace compost, was investigated. Antifungal susceptibility, particularly fluconazole susceptibility, was assessed, and the strain’s biotechnological potential by comparing its ability to utilize low-cost carbon sources, including SCG, with a natural isolate of Saccharomyces cerevisiae (strain ZMUM_K003) was assessed. The P. kudriavzevii strain ZMUM_K002 exhibited higher fluconazole susceptibility and yielded more than 30% more biomass in optimized media formulations compared to S. cerevisiae ZMUM_K003. These findings demonstrate that P. kudriavzevii ZMUM_K002 has the potential for efficient biomass production in sustainable industrial biotechnology, particularly in processes requiring high biomass yields on alternative substrates.
Keywords: Pichia kudriavzevii, Candida krusei, environmental sampling, biomass production, sauerkraut, safety assessment, spent coffee grounds
Published in DKUM: 21.03.2025; Views: 0; Downloads: 6
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2. A hierarchical knowledge graph embedding framework for link predictionShuang Liu, Chengwang Hou, Jiana Meng, Peng Chen, Simon Kolmanič, 2024, original scientific article Keywords: knowledge graph embedding, knowledge graph completion, negative sampling, link prediction
Published in DKUM: 04.02.2025; Views: 0; Downloads: 3
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3. Optimizing laser cutting of stainless steel using latin hypercube sampling and neural networksKristijan Šket, David Potočnik, Lucijano Berus, Jernej Hernavs, Mirko Ficko, 2025, original scientific article Abstract: Optimizing cutting parameters in fiber laser cutting of austenitic stainless steel is challenging due to the complex interplay of multiple variables and quality metrics. To solve this problem, Latin hypercube sampling was used to ensure a comprehensive and efficient exploration of the parameter space with a smaller number of trials (185), coupled with feedforward neural networks for predictive modeling. The networks were trained with a leave-oneout cross-validation strategy to mitigate overfitting. Different configurations of hidden layers, neurons, and training functions were used. The approach was focused on minimizing dross and roughness on both the top and bottom areas of the cut surfaces. During the testing phase, an average MSE of 0.063 and an average MAPE of 4.68% were achieved by the models. Additionally, an experimental test was performed on the best parameter settings predicted by the models. Initial modelling was conducted for each quality metric individually, resulting in an average percentage difference of 1.37% between predicted and actual results. Grid search was also per formed to determine an optimal input parameter set for all outputs, with predictions achieving an average ac curacy of 98.34%. Experimental validation confirmed the accuracy and robustness of the model predictions, demonstrating the effectiveness of the methodology in optimizing multiple parameters of complex laser cutting processes.
Keywords: laser cutting optimization, cut surface quality, dross formation, Latin hypercube sampling, feedforward neural network
Published in DKUM: 10.01.2025; Views: 0; Downloads: 22
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4. Advancements in data analysis for the work-sampling methodBorut Buchmeister, Nataša Vujica-Herzog, 2024, original scientific article Abstract: The work-sampling method makes it possible to gain valuable insights into what is happening in production systems. Work sampling is a process used to estimate the proportion of shift time that workers (or machines) spend on different activities (within productive work or losses). It is estimated based on enough random observations of activities over a selected period. When workplace operations do not have short cycle times or high repetition rates, the use of such a statistical technique is necessary because the labor sampling data can provide information that can be used to set standards. The work-sampling procedure is well standardized, but additional contributions are possible when evaluating the observations. In this paper, we present our contribution to improving the decision-making process based on work-sampling data. We introduce a correlation comparison of the measured hourly shares of all activities in pairs to check whether there are mutual connections or to uncover hidden connections between activities. The results allow for easier decision-making (conclusions) regarding the influence of the selected activities on the triggering of the others. With the additional calculation method, we can uncover behavioral patterns that would have been overlooked with the basic method. This leads to improved efficiency and productivity of the production system.
Keywords: work sampling, observations, analysis, proportions, correlations, interdependence between activities
Published in DKUM: 09.05.2024; Views: 204; Downloads: 24
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5. Role of human papillomavirus self-sampling in cervical cancer screeningTeodora Bokan, Iztok Takač, Alenka Repše-Fokter, Urška Ivanuš, Tine Jerman, Darja Arko, 2020, review article Keywords: self-sampling, Pap smear, screening
Published in DKUM: 23.01.2023; Views: 549; Downloads: 50
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6. Mitigating the conflict between pitfall-trap sampling and conservation of terrestrial subterranean communities in cavesPeter Kozel, Tanja Pipan, Nina Šajna, Slavko Polak, Tone Novak, 2017, original scientific article Abstract: Subterranean habitats are known for their rich endemic fauna and high vulnerability to disturbance. Many methods and techniques are used to sample the biodiversity of terrestrial invertebrate fauna in caves, among which pitfall trapping remains one of the most frequently used and effective ones. However, this method has turned out to be harmful to subterranean communities if applied inappropriately. Traditionally, pitfall traps have been placed in caves solely on the ground. Here we present an optimized technique of pitfall trapping to achieve a balance between sampling completeness and minimal disturbance of the fauna in the cave. Monthly we placed traps for two days in two parallel sets, a ground trap and an upper one−just below the ceiling−along the cave. In the upper set, about 10% additional species were recorded compared to the ground set. Greater species diversity in the cave was the consequence of both the increased sampling effort and the amplified heterogeneity of sampled microhabitats. In caves sampled by traditional pitfall trapping, overlooked species may be a consequence of methodological biases, leading to lower biodiversity estimates. In our research, incidence-based estimations mostly surpassed abundance-based ones and predicted 95% coverage of the species richness within about two years of sampling. The sampling used contributes at the same time to both the more effective and less invasive inventory of the subterranean fauna. Thus, it may serve as an optional sampling to achieve optimal balance between required data for biodiversity and ecological studies, and nature conservation goals.
Keywords: biodiversity estimators, microhabitats, sampling effort, sampling techniques, biological inventories
Published in DKUM: 30.10.2017; Views: 1362; Downloads: 398
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7. Statistics for business and economicsDavid Ray Anderson, Dennis J. Sweeney, Thomas Arthur Williams, Jim Freeman, Eddie ShoesmithKeywords: statistics, statistical methods, commercial business, economy, probability, distributions, sampling, analysis of variance, experimental design, regression analysis, forecasting, analysis
Published in DKUM: 06.06.2012; Views: 1654; Downloads: 40
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8. Statistics for economics, accounting and business studiesMichael Barrow, 2001, higher education textbook Keywords: economics, economy, statistical methods, statistics, computer science, computer application, software, computer programmes, data base, index numbers, indexes, probability, realibility, distributions, hypotheses testing, data, sampling, regression analysis, correlations, time series, mistakes, problem solving, solution of problems, statistical analysis, application, business process, accounting, cases, case study, textbooks, exercises
Published in DKUM: 01.06.2012; Views: 3006; Downloads: 60
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9. CD-ROM to accompany The data model resource bookLen SilverstonKeywords: information systems, MIS, data structure, data, warehousing, data warehousing, models, data base, CD-ROM, computer diskette, enterprise, products, ordering sets, business function, human resource management, human resources, sampling, design, application, modelling, electronic commerce
Published in DKUM: 01.06.2012; Views: 4116; Downloads: 174
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10. Contemporary business statistics with Microsoft Excel : (Microsoft Excel 2000 and Excel 97)David Ray Anderson, Dennis J. Sweeney, Thomas Arthur WilliamsKeywords: economics, economy, business operation, business operation of the enterprise, statistical methods, statistics, computer science, computer application, software, computer programmes, Excel, CD-ROM, compact disc, computer diskette, Internet, computer networks, data base, probability, realibility, distributions, hypotheses testing, data, sampling, regression analysis, correlations, time series, mistakes, problem solving, solution of problems, statistical analysis, application, business process, accounting, cas
Published in DKUM: 01.06.2012; Views: 2975; Downloads: 37
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