Reducing scrap and improving an air conditioning pipe production line

30th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2021) -15-18 June 2021, Athens, GreeceThe automotive industry is considered one of the most demanding and competitive sectors in the global market. This increasingly implies having a stable and optimized production process, always with a view to continuous improvement. Therefore, it is very important to be aware of all the waste that is generated in all production and logistics operations and take action to reduce them. In this regard and considering the process of producing air conditioning pipes for the automotive industry, a high scrap value was detected mainly due to soldering process. Therefore, the entire production process is analyzed in order to identify the main causes behind the high scrap value. Several Lean and quality tools are used to reduce not only the amount of scrap but also to increase the line productivity. In order to face this challenge, after elaborating the action plan and corresponding implementation, the scrap value is reduced by 12% in general, and productivity increased by 29%, 55% and 22.5% in three different references produced by the same machine. Although this solution is a bit expensive, the corresponding payback is reduced, so it can easily be applied transversally to other similar machines allowing extremely interesting gains in the short term.Andresa Baptista acknowledges the financial support of CIDEM- Research Center of Mechanical Engineering, FCT –Portuguese Foundation for the Development of Science and Technology, Ministry of Science, Technology and Higher ducation, under the Project UID/EMS/0615/2019.info:eu-repo/semantics/publishedVersio

Numerical and Experimental Investigation of Laminar One-Dimensional Counter-Flow Flames Using Product Gas From Pyrolysis and Gasification of Woody Biomass

Further advances in the utilization of biomass-based gaseous fuels in combustion systems require a deeper understanding of the combustion chemistry behind, as well as of the coupling of the chemistry with physical phenomena such as turbulence. The former is investigated in the present study combining both experiments with numerical simulations of different types of laminar non-premixed flames (sooting and non-sooting) in a counter-flow setup. The focus is put on synthetic gas mixtures, resembling, to different extents, typical compositions of the product gas obtained in biomass gasification consisting of CH4 (reference) and CH4 mixed with CO2, N2, O2, and/or H2, always. The oxidizer in all cases is air. A wide range of air-fuel ratios is considered. The influence of the product gas composition on the flame behaviour and flame structure with respect to the changes of the species profiles and peak temperatures with changing flow velocities is discussed. Laser-based spectroscopy techniques, in particular laser-induced Rayleigh scattering and laser-induced fluorescence (LIF), are applied as diagnostic tools. The former can provide an accurate understanding of temperature distributions, while the latter helps to identify the flame front through the tracking of intermediate species, such as CH2O (formaldehyde). Additionally, CH* chemiluminescence contributes to localize the flame front. Lastly, the influence of the N2-shroud flow velocities and diameters, as well as resulting buoyancy effects due to a raise in temperature, are taken into account. In correspondence to these experiments, the flames are numerically simulated by an in-house time-dependent implicit Fortran code

Nitrate reduction capacity of the oral microbiota is impaired in periodontitis: potential implications for systemic nitric oxide availability

The reduction of nitrate to nitrite by the oral microbiota has been proposed to be important for oral health and results in nitric oxide formation that can improve cardiometabolic conditions. Studies of bacterial composition in subgingival plaque suggest that nitrate-reducing bacteria are associated with periodontal health, but the impact of periodontitis on nitrate-reducing capacity (NRC) and, therefore, nitric oxide availability has not been evaluated. The current study aimed to evaluate how periodontitis affects the NRC of the oral microbiota. First, 16S rRNA sequencing data from five different countries were analyzed, revealing that nitrate-reducing bacteria were significantly lower in subgingival plaque of periodontitis patients compared with healthy individuals (P < 0.05 in all five datasets with n = 20–82 samples per dataset). Secondly, subgingival plaque, saliva, and plasma samples were obtained from 42 periodontitis patients before and after periodontal treatment. The oral NRC was determined in vitro by incubating saliva with 8 mmol/L nitrate (a concentration found in saliva after nitrate-rich vegetable intake) and compared with the NRC of 15 healthy individuals. Salivary NRC was found to be diminished in periodontal patients before treatment (P < 0.05) but recovered to healthy levels 90 days post-treatment. Additionally, the subgingival levels of nitrate-reducing bacteria increased after treatment and correlated negatively with periodontitis-associated bacteria (P < 0.01). No significant effect of periodontal treatment on the baseline saliva and plasma nitrate and nitrite levels was found, indicating that differences in the NRC may only be revealed after nitrate intake. Our results suggest that an impaired NRC in periodontitis could limit dietary nitrate-derived nitric oxide levels, and the effect on systemic health should be explored in future studies

Impact of abiotic factors and husbandry on saprolegniosis in salmonid farms

Oomycetes of the genus Saprolegnia are widespread in freshwater environment and are among the main path- ogens causing economic losses in salmonid aquaculture. Infections by mycotic agents in fish farming are generally considered to result from chronic stress and poor fish condition associated with water quality problems, adverse environmental conditions, frequent/rough/incorrect handling, concurrent infections, physiological changes associated with reproduction and immunocompromised animals. To identify risk factors for Saprolegnia infections in trout and Atlantic salmon farming, longitudinal studies were carried out in different Italian, Spanish, and Scottish fish farms. Prevalence of saprolegniosis and fish mortality were monitored over time and statistically analysed with respect to husbandry and environmental factors. Overall, statistical results by production cycle (trout vs salmon farming) and by country indicate that the prevalence of Saprolegnia may be influenced by peculiarities of the culture system and farming environment. Nevertheless, a specific set of parameters, including lower water temperature, and handling procedures increased Saprolegnia prevalence in all the considered farms. Particularly, in trout farms Saprolegnia infections represented an important contribution to mortality, and prevalence was influenced by water temperature and pH, and by fish density within the tanks. Similarly, temperature and water quality were the main factors influencing the prev- alence of Saprolegnia in Atlantic salmon farms. Moreover, molecular analyses confirmed the role of S. parasitica as the main pathogenic oomycete in trout and salmon farming in the considered countries. The identification of risk factors for introduction and increase of Saprolegnia infection in fish farms will allow the correct design of bio- security and pathogen control strategie

Genetic dissection of the tissue‐specific roles of type III effectors and phytotoxins in the pathogenicity of Pseudomonas syringae pv. syringae to cherry

When compared with other phylogroups (PGs) of the Pseudomonas syringae species complex, P. syringae pv. syringae (Pss) strains within PG2 have a reduced repertoire of type III effectors (T3Es) but produce several phytotoxins. Effectors within the cherry pathogen Pss 9644 were grouped based on their frequency in strains from Prunus as the conserved effector locus (CEL) common to most P. syringae pathogens; a core of effectors common to PG2; a set of PRUNUS effectors common to cherry pathogens; and a FLEXIBLE set of T3Es. Pss 9644 also contains gene clusters for biosynthesis of toxins syringomycin, syringopeptin and syringolin A. After confirmation of virulence gene expression, mutants with a sequential series of T3E and toxin deletions were pathogenicity tested on wood, leaves and fruits of sweet cherry (Prunus avium) and leaves of ornamental cherry (Prunus incisa). The toxins had a key role in disease development in fruits but were less important in leaves and wood. An effectorless mutant retained some pathogenicity to fruit but not wood or leaves. Striking redundancy was observed amongst effector groups. The CEL effectors have important roles during the early stages of leaf infection and possibly acted synergistically with toxins in all tissues. Deletion of separate groups of T3Es had more effect in P. incisa than in P. avium. Mixed inocula were used to complement the toxin mutations in trans and indicated that strain mixtures may be important in the field. Our results highlight the niche‐specific role of toxins in P. avium tissues and the complexity of effector redundancy in the pathogen Pss 9644

Belle II Technical Design Report

The Belle detector at the KEKB electron-positron collider has collected almost 1 billion Y(4S) events in its decade of operation. Super-KEKB, an upgrade of KEKB is under construction, to increase the luminosity by two orders of magnitude during a three-year shutdown, with an ultimate goal of 8E35 /cm^2 /s luminosity. To exploit the increased luminosity, an upgrade of the Belle detector has been proposed. A new international collaboration Belle-II, is being formed. The Technical Design Report presents physics motivation, basic methods of the accelerator upgrade, as well as key improvements of the detector.Comment: Edited by: Z. Dole\v{z}al and S. Un

Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Re-annotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi

Automatic Individual Identification of Patterned Solitary Species Based on Unlabeled Video Data

The manual processing and analysis of videos from camera traps is time-consuming and includes several steps, ranging from the filtering of falsely triggered footage to identifying and re-identifying individuals. In this study, we developed a pipeline to automatically analyze videos from camera traps to identify individuals without requiring manual interaction. This pipeline applies to animal species with uniquely identifiable fur patterns and solitary behavior, such as leopards (Panthera pardus). We assumed that the same individual was seen throughout one triggered video sequence. With this assumption, multiple images could be assigned to an individual for the initial database filling without pre-labeling. The pipeline was based on well-established components from computer vision and deep learning, particularly convolutional neural networks (CNNs) and scale-invariant feature transform (SIFT) features. We augmented this basis by implementing additional components to substitute otherwise required human interactions. Based on the similarity between frames from the video material, clusters were formed that represented individuals bypassing the open set problem of the unknown total population. The pipeline was tested on a dataset of leopard videos collected by the Pan African Programme: The Cultured Chimpanzee (PanAf) and achieved a success rate of over 83% for correct matches between previously unknown individuals. The proposed pipeline can become a valuable tool for future conservation projects based on camera trap data, reducing the work of manual analysis for individual identification, when labeled data is unavailable

Persistent anthrax as a major driver of wildlife mortality in a tropical rainforest

Anthrax is a globally important animal disease and zoonosis. Despite this, our current knowledge of anthrax ecology is largely limited to arid ecosystems, where outbreaks are most commonly reported. Here we show that the dynamics of an anthrax-causing agent, Bacillus cereus biovar anthracis, in a tropical rainforest have severe consequences for local wildlife communities. Using data and samples collected over three decades, we show that rainforest anthrax is a persistent and widespread cause of death for a broad range of mammalian hosts. We predict that this pathogen will accelerate the decline and possibly result in the extirpation of local chimpanzee (Pan troglodytes verus) populations. We present the epidemiology of a cryptic pathogen and show that its presence has important implications for conservation