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This study examines flank wear and surface ruoghness in up and down hard end milling. After obtaining the mathematical models, it has been carried out a series of numerical simulations with variation of input parameters in order to analyze their influence on flank wear and surface roughness. Additionally, flank wear and surface roughness has been analysed in correlation with the volume of the removed material for different cutting parameters. Observed from the viewpoint of machinability, down hard milling is favorable compared to the up hard milling. [ABSTRACT FROM AUTHOR]

The objective of this paper is the analysis and evaluation of the quality of the new flux-cored wire designed for the MAG welding process that was developed and produced using special laboratory equipment. Experimental welding was performed with the new activated flux-cored wire and classic solid wire with changing of welding parameters and shielding gas composition (100 % CO2 and gas mixtures of Ar + CO2 + O2). [ABSTRACT FROM AUTHOR]

In this paper, the influence of the activating flux on the weld joint properties at the drawn arc stud welding process with ceramic ferrule is analysed. In the experimental part of the paper, the arc stud welding process is applied with the application of the activating flux for ATIG process. In order to evaluate the influence of the activating flux on the welding process parameters variations, the main welding parameters were monitored by an on-line monitoring system. Besides monitoring of welding current and voltage, the influence of the activating flux on the weld joint appearance is investigated. The macrosections of the weld joints welded with the same parameters, but with and without the presence of activating flux are shown. [ABSTRACT FROM AUTHOR]

This paper examines the influence of cutting parameters on surface roughness of steel workpiece. The experiments have been carried out in accordance with a design of experiments (DOE). Equation for the surface roughness, as a function of cutting parameters, has been obtained by means of regression analysis. To obtain the minimal value of surface roughness, the equation optimizing was performed by using partial derivations and solving system of equations. The Taguchi method, with orthogonal arrays and signal to noise ratio, has been used to analyse impact of various cutting parameters on surface roughness and to find optimal levels of the cutting parameters. The comparison of results obtained by means of the response surface method and the Taguchi method was performed. [ABSTRACT FROM AUTHOR]

The paper presents a novel approach to frame-alignment analysis. A universal model for out-of-frame procedures is presented and statistical parameters are derived. The syncronisation pattern structure is analysed using the bifix indicators. Different parameters for in- and out-offrame procedures are considered. The results are applied to the STM-1 frame, for which the optimal framing strategy is proposed. [ABSTRACT FROM AUTHOR]

In this paper the results of the research about the influence of the impurities on the depth of penetration with carbon steels weldings of different chemical composition are presented. These data suggest that presence of those impurities, such as sulphure and oxygen, in the steel, increases the depth of penetration to 1,3 - 1,5 times compared to welding reĀned steels. Applying activating fluxes for welding high t ensile steels, provides an increase in the depth of penetration of 2 - 3 times. [ABSTRACT FROM AUTHOR]

Artificial objects, particularly tunnels used for water transport under pressure, impact the geological and hydrogeological environment to a greater or lesser extent, and it is vital to assess their contributions to groundwater quality. Although tunnels are typically lined with concrete, their interaction with the hydrogeological environment intensifies over time. In this study, the detailed spatiotemporal monitoring of all hydrogeological features within the potential influence zone of the hydraulic tunnel of the Pirot Hydropower Plant has been conducted in order to determine the degree of interaction between the artificial object and the natural environment in real time, and to assess the correlation between monitored parameters. Natural conditions of the environment were defined, as well as potential changes through the observing groundwater regimes. The monitoring network included observations of groundwater regimes at seven springs located in close proximity to the hydraulic tunnel, within the tunnel, at three piezometers, and along the river, while methods employed were hydrological monitoring, physicochemical monitoring, and groundwater piezometer sensing. Cross-correlation analysis has been applied for assessing the impact of precipitation dynamics on the spring discharge regime. The results indicate a direct influence of the tunnel on the hydrogeological environment, proving the consistency and high correlation between the monitored parameters.

This study examines the impact of cutting regimes on determining cutting resistance in the processing of polypropylene (PP) using the CNC lathe EMCO F5. The rationale for this research stems from polypropylene's rarity among thermoplastics in possessing structural stability, allowing for its comparison to metals and practical application in products replacing metal parts. Leveraging its favorable mechanical properties, polypropylene finds utility in producing parts subject to dynamic loads, boasting high resistance to impact loads-particularly undesirable in machining. An advantageous characteristic of polypropylene is its affordability, rendering it an economical choice across numerous applications. Despite these merits, polypropylene's exploration in cutting processing remains limited, underscoring the novelty of this research endeavor. The main method for determining cutting resistance involves measuring electric current strength during processing. This direct measurement, facilitated by input cutting regime parameters, is recorded by the PLC controller, with the current value extracted from the machine tool's ammeter. The experimental approach entails varying cutting regime parameters-cutting speed (v), feed rate (s), and depth of cut (a)-across minimum and maximum values, recognized as pivotal factors influencing cutting force development and the attainment of the desired machined surface quality.

Mainstream research on information theory within the field of living systems involves the application of analytical tools to understand a broad range of life processes. This paper is dedicated to an opposite problem: it explores the information theory and communication engineering methods that have counterparts in the data transmission process by way of DNA structures and neural fibers. Considering the requirements of modern multimedia, transmission methods chosen by nature may be different, suboptimal, or even far from optimal. However, nature is known for rational resource usage, so its methods have a significant advantage: they are proven to be sustainable. Perhaps understanding the engineering aspects of methods of nature can inspire a design of alternative green, stable, and low-cost transmission.

Microbial strategies for resource use are an essential determinant of their fitness in complex habitats. When facing environments with multiple nutrients, microbes often use them sequentially according to a preference hierarchy, resulting in well-known patterns of diauxic growth. In theory, the evolutionary diversification of metabolic hierarchies could represent a mechanism supporting coexistence and biodiversity by enabling temporal segregation of niches. Despite this ecologically critical role, the extent to which substrate preference hierarchies can evolve and diversify remains largely unexplored. Here, we used genome-scale metabolic modeling to systematically explore the evolution of metabolic hierarchies across a vast space of metabolic network genotypes. We find that only a limited number of metabolic hierarchies can readily evolve, corresponding to the most commonly observed hierarchies in genome-derived models. We further show how the evolution of novel hierarchies is constrained by the architecture of central metabolism, which determines both the propensity to change ranks between pairs of substrates and the effect of specific reactions on hierarchy evolution. Our analysis sheds light on the genetic and mechanistic determinants of microbial metabolic hierarchies, opening new research avenues to understand their evolution, evolvability, and ecology., (© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

Harnessing the power of microbial consortia is integral to a diverse range of sectors, from healthcare to biotechnology to environmental remediation. To fully realize this potential, it is critical to understand the mechanisms behind the interactions that structure microbial consortia and determine their functions. Constraint-based reconstruction and analysis (COBRA) approaches, employing genome-scale metabolic models (GEMs), have emerged as the state-of-the-art tool to simulate the behavior of microbial communities from their constituent genomes. In the last decade, many tools have been developed that use COBRA approaches to simulate multi-species consortia, under either steady-state, dynamic, or spatiotemporally varying scenarios. Yet, these tools have not been systematically evaluated regarding their software quality, most suitable application, and predictive power. Hence, it is uncertain which tools users should apply to their system and what are the most urgent directions that developers should take in the future to improve existing capacities. This study conducted a systematic evaluation of COBRA-based tools for microbial communities using datasets from two-member communities as test cases. First, we performed a qualitative assessment in which we evaluated 24 published tools based on a list of FAIR (Findability, Accessibility, Interoperability, and Reusability) features essential for software quality. Next, we quantitatively tested the predictions in a subset of 14 of these tools against experimental data from three different case studies: a) syngas fermentation by C. autoethanogenum and C. kluyveri for the static tools, b) glucose/xylose fermentation with engineered E. coli and S. cerevisiae for the dynamic tools, and c) a Petri dish of E. coli and S. enterica for tools incorporating spatiotemporal variation. Our results show varying performance levels of the best qualitatively assessed tools when examining the different categories of tools. The differences in the mathematical formulation of the approaches and their relation to the results were also discussed. Ultimately, we provide recommendations for refining future GEM microbial modeling tools., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: AH is one of the developers of the Microbiome Toolbox. JZ is one of the developers of BacArena. DB is one of the developers of COMETS., (Copyright: © 2023 Scott et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Various biomarkers like certain complete blood cell count parameters and the derived ratios including neutrophil-lymphocyte ratio are commonly used to evaluate disease severity. Our study aimed to establish if baseline levels of complete blood cell count-derived biomarkers and CRP, measured before any treatment which can interfere with their values, could serve as a predictor of development of pneumonia and the need for hospitalization requiring oxygen therapy. We retrospectively analyzed the laboratory data of 200 consecutive patients without comorbidities, who denied usage of medications prior to blood analysis and visited a COVID-19 ambulance between October and December 2021. Multivariate regression analysis extracted older age, elevated CRP and lower eosinophil count as significant independent predictors of pneumonia ( p = 0.003, p = 0.000, p = 0.046, respectively). Independent predictors of hospitalization were higher CRP ( p = 0.000) and lower platelet count ( p = 0.005). There was no significant difference in the neutrophil-lymphocyte and platelet-lymphocyte ratios between examined groups. Individual biomarkers such as platelet and eosinophil count might be better in predicting the severity of COVID-19 than the neutrophil-lymphocyte and platelet-lymphocyte ratios.

Understanding the mechanisms that maintain microbial biodiversity is a critical aspiration in ecology. Past work on microbial coexistence has largely focused on species pairs, but it is unclear whether pairwise coexistence in isolation is required for coexistence in a multispecies community. To address this question, we conducted hundreds of pairwise competition experiments among the stably coexisting members of 12 different enrichment communities in vitro. To determine the outcomes of these experiments, we developed an automated image analysis pipeline to quantify species abundances. We found that competitive exclusion was the most common outcome, and it was strongly hierarchical and transitive. Because many species that coexist within a stable multispecies community fail to coexist in pairwise co-culture under identical conditions, we concluded that multispecies coexistence is an emergent phenomenon. This work highlights the importance of community context for understanding the origins of coexistence in complex ecosystems.

The latest trends in machining research show that great efforts are being made to simulate machining processes. This paper presents the results of cutting force, feed force and temperatures when the orthogonal cutting of EN AW 6082 T6 alloy. Appropriate material model and damage model were investigated in order to perform finite element simulation with Coupled Eulerian-Lagrangian (CEL) approach. In the next step, simulations were designed based on the input parameters. The size of element in the x -direction (2 μm-10 μm), size of element in y -direction (2 μm-10 μm) and width of the workpiece (2 μm-100 μm) are considered as controllable variables The Genetic Algorithm was used to identify the optimal process parameters by which the minimum value of cutting force error, the minimum value of feed force error and minimum simulation time will be achieved. The optimal combination of the process parameters is size of elements at x -direction 8 μm, y -direction 10 μm and width of workpiece 84 μm. By utilizing the optimal input parameters cutting force error was reduced from 6.5% to 1.07% and feed force error was reduced from 6.15% to 3.12%. The results showed that the optimum size and orientation of the finite element mesh can significantly reduce the error in the prediction of cutting forces and reduce processing simulation time. In addition, it was concluded that with the CEL approach, temperatures in the cutting zone can be successfully predicted., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors.)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic and one group of patients has developed a severe form of COVID-19 pneumonia with an urgent need for hospitalization and intensive care unit (ICU) admission. The aim of our study was to evaluate the prognostic role of MDW, CRP, procalcitonin (PCT), and lactate in critically ill COVID-19 patients. The primary outcome of interest is the 28 day mortality of ICU patients with confirmed SARS-CoV-2 infection and sepsis (according to Sepsis 3 criteria with acute change in SOFA score ≥ 2 points). Patients were divided into two groups according to survival on the 28th day after admission to the ICU. Every group was divided into two subgroups (women and men). Nonparametric tests (Mann-Whitney) for variables age, PCT, lactate, and MDW were lower than alpha p < 0.05, so there was a significant difference between survived and deceased patients. The Chi-square test confirmed statistically significant higher values of MDW and lactate in the non-survivor group. We found a significant association between MDW, lactate, procalcitonin, and fatal outcome, higher values were reported in the deceased group., Competing Interests: The authors declare no conflict of interest.

For microbiome biology to become a more predictive science, we must identify which descriptive features of microbial communities are reproducible and predictable, which are not, and why. We address this question by experimentally studying parallelism and convergence in microbial community assembly in replicate glucose-limited habitats. Here, we show that the previously observed family-level convergence in these habitats reflects a reproducible metabolic organization, where the ratio of the dominant metabolic groups can be explained from a simple resource-partitioning model. In turn, taxonomic divergence among replicate communities arises from multistability in population dynamics. Multistability can also lead to alternative functional states in closed ecosystems but not in metacommunities. Our findings empirically illustrate how the evolutionary conservation of quantitative metabolic traits, multistability, and the inherent stochasticity of population dynamics, may all conspire to generate the patterns of reproducibility and variability at different levels of organization that are commonplace in microbial community assembly., Competing Interests: Declaration of interests A.S. is a member of the Cell Systems Advisory Board. The authors otherwise declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Approximate and sample entropies are acclaimed tools for quantifying the regularity and unpredictability of time series. This paper analyses the causes of their inconsistencies. It is shown that the major problem is a coarse quantization of matching probabilities, causing a large error between their estimated and true values. Error distribution is symmetric, so in sample entropy, where matching probabilities are directly summed, errors cancel each other. In approximate entropy, errors are accumulating, as sums involve logarithms of matching probabilities. Increasing the time series length increases the number of quantization levels, and errors in entropy disappear both in approximate and in sample entropies. The distribution of time series also affects the errors. If it is asymmetric, the matching probabilities are asymmetric as well, so the matching probability errors cease to be mutually canceled and cause a persistent entropy error. Despite the accepted opinion, the influence of self-matching is marginal as it just shifts the error distribution along the error axis by the matching probability quant. Artificial lengthening the time series by interpolation, on the other hand, induces large error as interpolated samples are statistically dependent and destroy the level of unpredictability that is inherent to the original signal.

Genome-scale stoichiometric modeling of metabolism has become a standard systems biology tool for modeling cellular physiology and growth. Extensions of this approach are emerging as a valuable avenue for predicting, understanding and designing microbial communities. Computation of microbial ecosystems in time and space (COMETS) extends dynamic flux balance analysis to generate simulations of multiple microbial species in molecularly complex and spatially structured environments. Here we describe how to best use and apply the most recent version of COMETS, which incorporates a more accurate biophysical model of microbial biomass expansion upon growth, evolutionary dynamics and extracellular enzyme activity modules. In addition to a command-line option, COMETS includes user-friendly Python and MATLAB interfaces compatible with the well-established COBRA models and methods, as well as comprehensive documentation and tutorials. This protocol provides a detailed guideline for installing, testing and applying COMETS to different scenarios, generating simulations that take from a few minutes to several days to run, with broad applicability to microbial communities across biomes and scales., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Microorganisms display a stunning metabolic diversity. Understanding the origin of this diversity requires understanding how macroevolutionary processes such as innovation and diversification play out in the microbial world. Metabolic networks, which govern microbial resource use, can evolve through different mechanisms, e.g., horizontal gene transfer or de novo evolution of enzymes and pathways. This process is governed by a combination of environmental factors, selective pressures, and the constraints imposed by the genetic architecture of metabolic networks. In addition, many independent results hint that the process of niche construction, by which organisms actively modify their own and each other's niches and selective pressures, could play a major role in microbial innovation and diversification. Yet, the general principles by which niche construction shapes microbial macroevolutionary patterns remain largely unexplored. Here, we discuss several new hypotheses and directions, and suggest metabolic modeling methods that could allow us to explore large-scale empirical genotype-phenotype-(G-P)-environment spaces in order to study the macroevolutionary effects of niche construction. We hope that this short piece will further stimulate a systematic and quantitative characterization of macroevolutionary patterns and processes in microbial metabolism., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Bajić, Rebolleda-Gómez, Muñoz and Sánchez.)

Cardiomyopathy resistant to treatment is the most serious adverse effect of doxorubicin (dox). The mechanisms of dox-induced cardiomyopathy (DCM) have been extensively studied in dilated forms of DCM. However, efficient treatment did not emerge. The aim of the present work was to revisit the experimental model of DCM in rats, to define phenotype/s and associate them to the changes in cardiac transcriptome. Male Wistar rats equipped with radiotelemetry device, were randomized in DOX group (5 mg/0,5 mL/kg, IV dox; n = 18) and CONT group (0,5 mL/kg IV saline; n = 6). Echocardiography, autonomic spectral markers and baroreceptor reflex evaluation was performed prior to, and after treatment. Blood samples were collected at the end of experimentation. Cardiac, renal and hepatic tissues were analysed post-mortem by histology. Changes in expression of key cardiac genes affected by dox were assessed by RT-qPCR. Phenotypes were identified by clustering non-redundant features using four different algorithms averaged by evidence accumulation cluster technique. The results emphasize the existence of two major phenotypes of DCM with comparably high mortality rates: phenotype 1 characterized by, left ventricular (LV) dilatation, thinning of LV posterior wall, reduced LV ejection fraction (LVEF) and fractional shortening (LVFS), decreased HR variability (HRV), decreased baroreceptor effectiveness index (BEI) and increased NT-proBNP; and phenotype 2 with LV hypertrophy - increased LV mass, preserved LVEF, LVFS, no changes in HRV and BEI and moderate NT-proBNP increase. Both phenotypes exhibited a genetic shift to a new-born program., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Redox couples coordinate cellular function, but the consequences of their imbalances are unclear. This is somewhat associated with the limitations of their experimental quantification. Here we circumvent these difficulties by presenting an approach that characterizes fitness-based tolerance profiles to redox couple imbalances using an in silico representation of metabolism. Focusing on the NADH/NAD + redox couple in yeast, we demonstrate that reductive disequilibria generate metabolic syndromes comparable to those observed in cancer cells. The tolerance of yeast mutants to redox disequilibrium can also explain 30% of the variability in their experimentally measured chronological lifespan. Moreover, by predicting the significance of some metabolites to help stand imbalances, we correctly identify nutrients underlying mechanisms of pathology, lifespan-protecting molecules, or caloric restriction mimetics. Tolerance to redox imbalances becomes, in this way, a sound framework to recognize properties of the aging phenotype while providing a consistent biological rationale to assess anti-aging interventions., Competing Interests: The authors declare no competing interests., (© 2021 The Author(s).)

Onions are one of the most widely grown vegetable crops. As production increases, so does the generation of waste from various parts of the onion, raising the need for efficient ecological disposal and use of such waste products. However, onion waste products are a rich source of antioxidants with a range of biological properties, therefore, they could potentially be used in food and pharmaceutical industries. In the present study, we identified the main flavonols and anthocyanins in peel extracts of Allium × cornutum Clement ex Visiani, 1842, and two varieties of Allium cepa L. and tested their antioxidant, antimicrobial and antiproliferative properties. Quercetin 3,4'-diglucolside, quercetin 4'-monoglucoside and quercetin are the most abundant flavonols in all onion extracts detected by high-performance liquid chromatography (HPLC) method. The composition of anthocyanins varied in all extracts. 2,2'-diphenyl-1-picrylhydrazyl (DPPH) and oxygen radical absorbance capacity (ORAC) assays showed that the triploid onion A. × cornutum had the highest antioxidant power. Evaluation of antimicrobial activity by broth microdilution assay also showed that A. × cornutum had higher antimicrobial activity compared to the red and yellow onion varieties. Comparable antiproliferative activity was confirmed for all onion extracts tested on three cancer cell lines: Hela (cervical cancer cell line), HCT116 (human colon cancer cell line) and U2OS (human osteosarcoma cell line). The most abundant onion flavonols (quercetin 3,4'-diglucoside and quercetin 4'-monoglucoside) showed weaker antimicrobial as well as antiproliferative properties compared to the extracts, leading to the conclusion that other phytochemicals besides flavonols contribute to the biological activity of onion peel extracts. The results demonstrate the antioxidant and antimicrobial properties of onion peels, which have promising potential as cancer cell proliferation inhibitors.