In budding yeast, the neck that connects the mother and daughter cell is the site of essential functions such as organelle trafficking, septum formation and cytokinesis. Therefore, the morphology of ...this region, which depends on the surrounding cell wall, must be maintained throughout the cell cycle. Growth at the neck is prevented, redundantly, by a septin ring inside the cell membrane and a chitin ring in the cell wall. Here, we describe recent work supporting the hypothesis that attachment of the chitin ring, which forms at the mother-bud neck during budding, to β-1,3-glucan in the cell wall is necessary to stop growth at the neck. Thus, in this scenario, chemistry controls morphogenesis.
•Overview of modeling approaches, formulations, problem classes, and solution techniques.•Overview of methods for uncertainty mitigation.•Overview of tools for modeling, co-simulation, control ...design, and optimization.•A unified framework with focus on the real-world applications.•Standardized control performance assessment methodology.
It has been proven that advanced building control, like model predictive control (MPC), can notably reduce the energy use and mitigate greenhouse gas emissions. However, despite intensive research efforts, the practical applications are still in the early stages. There is a growing need for multidisciplinary education on advanced control methods in the built environment to be accessible for a broad range of researchers and practitioners with different engineering backgrounds. This paper provides a unified framework for model predictive building control technology with focus on the real-world applications. From a theoretical point of view, this paper presents an overview of MPC formulations for building control, modeling paradigms and model types, together with algorithms necessary for real-life implementation. The paper categorizes the most notable MPC problem classes, links them with corresponding solution techniques, and provides an overview of methods for mitigation of the uncertainties for increased performance and robustness of MPC. From a practical point of view, this paper delivers an elaborate classification of the most important modeling, co-simulation, optimal control design, and optimization techniques, tools, and solvers suitable to tackle the MPC problems in the context of building climate control. On top of this, the paper presents the essential components of a practical implementation of MPC such as different control architectures and nuances of communication infrastructures within supervisory control and data acquisition (SCADA) systems. The paper draws practical guidelines with a generic workflow for implementation of MPC in real buildings aimed for contemporary adopters of this technology. Finally, the importance of standardized performance assessment and methodology for comparison of different building control algorithms is discussed.
Purpose
The purpose of this paper is to examine the adoption of e-banking in Colombia, including a comprehensive analysis of consumer trust in this type of transaction and of the impact of the ...current government policy to promote e-commerce.
Design/methodology/approach
An empirical investigation based on the UTAUT2 model collected data from throughout the country to develop 600 online questionnaires.
Findings
The proposed model was validated in that the factors hypothesised to build trust in the use of electronic banking were shown to be significant: trust, performance expectancy and effort expectancy had a positive impact on the use of financial websites in Colombia, while government support did not have a significant impact.
Research limitations/implications
The study explains the antecedents to trust, as well as the government support variable, and concludes by producing a model that is highly successful in predicting financial customers’ online behaviour.
Practical implications
The results can help Colombia’s Government and private banks to further develop trust and other conditions necessary for e-banking.
Social implications
Studies on the adoption of electronic banking provide users of these services solutions for their needs. Government policies to support the development of e-banking are not viewed favourably by Colombians.
Originality/value
This study is one of the first to present empirical findings on the acceptance of e-banking in Latin America; it further presents a model that integrates the most important variables needed for an analysis of the acceptance of e-banking.
The aim of our study was to evaluate the diagnostic performance of two antigen rapid diagnostic tests (Ag‐RDTs) to diagnose severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection. We ...evaluated Panbio and SD‐Biosensor Ag‐RDTs. We employed 186 polymerase chain reaction (PCR) negative samples to evaluate the specificity and 170 PCR positive samples to assess the sensitivity. We evaluated their sensitivity according to Cycle threshold (C
t) values and days post onset of symptoms (d.p.o.). Tests were compared using the McNemar's test. Agreement was evaluated using the kappa score. Specificity was 100% for Panbio and 97.3% for SD‐Biosensor. Sensitivity for samples with C
t ≤ 20 was 100% for both assays and for samples with C
t = 20–25 was 93.0% (Panbio) and 95.3% (SD‐Biosensor) (p = 1.000). Sensitivity decreased for samples wit C
t = 25–30 (Panbio: 41.3%, SD‐Biosensor: 52.2%, p = 0.125) and samples with C
t ≥ 30 (Panbio: 5.0%, SD‐Biosensor: 17.5%, p = 0.063). Sensitivity within seven d.p.o. was 87.7% for Panbio and 90.4% for SD‐Biosensor and notably decreased after seven d.p.o. Agreement with PCR was excellent for high viral load samples (C
t ≤ 25): Panbio, 98.9%, kappa = 0.974; SD‐Biosensor, 97.4%, kappa = 0.940. Agreement between Ag‐RDTs was excellent (94.9%, kappa = 0.882). Panbio and SD‐Biosensor Ag‐RDTs showed excellent agreement and diagnostic performance results for samples with high viral loads (C
t ≤ 25) or samples within seven d.p.o.
Highlights
Panbio and SD‐Biosensor Ag‐RDTs are reliable to diagnose SARS‐CoV‐2 infection.
They showed high specificity: 100% (Panbio) and 97.3% (SD‐Biosensor).
Sensitivity for samples with Ct ≤ 20 was 100% and for samples with Ct ≤ 25 was over 93%.
Their sensitivity was over 87% within 7 days after symptoms onset. Agreement between them was excellent (agreement = 94.9%, kappa = 0.882).
Summary
The cross‐linking of polysaccharides to assemble new cell wall in fungi requires transglycosylation mechanisms by which preexisting glycosidic linkages are broken and new linkages are created ...between the polysaccharides. The molecular mechanisms for these processes, which are essential for fungal cell biology, are only now beginning to be elucidated. Recent development of in vivo and in vitro biochemical approaches has allowed characterization of important aspects about the formation of chitin–glucan covalent cell wall cross‐links by cell wall transglycosylases of the CRH family and their biological function. Covalent linkages between chitin and glucan mediated by Crh proteins control morphogenesis and also play important roles in the remodeling of the fungal cell wall as part of the compensatory responses necessary to counterbalance cell wall stress. These enzymes are encoded by multigene families of redundant proteins very well conserved in fungal genomes but absent in mammalian cells. Understanding the molecular basis of fungal adaptation to cell wall stress through these and other cell wall remodeling enzymatic activities offers an opportunity to explore novel antifungal treatments and to identify potential fungal virulence factors.
Mean-variance portfolio optimization models are sensitive to uncertainty in risk-return estimates, which may result in poor out-of-sample performance. In particular, the estimates may suffer when the ...number of assets considered is high and the length of the return time series is not sufficiently long. This is precisely the case in the cryptocurrency market, where there are hundreds of crypto assets that have been traded for a few years. We propose enhancing the mean-variance (MV) model with a pre-selection stage that uses a prototype-based clustering algorithm to reduce the number of crypto assets considered at each investment period. In the pre-selection stage, we run a prototype-based clustering algorithm where the assets are described by variables representing the profit-risk duality. The prototypes of the clustering partition are automatically examined and the one that best suits our risk-aversion preference is selected. We then run the MV portfolio optimization with the crypto assets of the selected cluster. The proposed approach is tested for a period of 17 months in the whole cryptocurrency market and two selections of the cryptocurrencies with the higher market capitalization (175 and 250 cryptos). We compare the results against three methods applied to the whole market: classic MV, risk parity, and hierarchical risk parity methods. We also compare our results with those from investing in the market index CCI30. The simulation results generally favor our proposal in terms of profit and risk-profit financial indicators. This result reaffirms the convenience of using machine learning methods to guide financial investments in complex and highly-volatile environments such as the cryptocurrency market.
Since the emergence of Bitcoin, cryptocurrencies have grown significantly, not only in terms of capitalization but also in number. Consequently, the cryptocurrency market can be a conducive arena for ...investors, as it offers many opportunities. However, it is difficult to understand. This study aims to describe, summarize, and segment the main trends of the entire cryptocurrency market in 2018, using data analysis tools. Accordingly, we propose a new clustering-based methodology that provides complementary views of the financial behavior of cryptocurrencies, and one that looks for associations between the clustering results, and other factors that are not involved in clustering. Particularly, the methodology involves applying three different partitional clustering algorithms, where each of them use a different representation for cryptocurrencies, namely, yearly mean, and standard deviation of the returns, distribution of returns that have not been applied to financial markets previously, and the time series of returns. Because each representation provides a different outlook of the market, we also examine the integration of the three clustering results, to obtain a fine-grained analysis of the main trends of the market. In conclusion, we analyze the association of the clustering results with other descriptive features of cryptocurrencies, including the age, technological attributes, and financial ratios derived from them. This will help to enhance the profiling of the clusters with additional descriptive insights, and to find associations with other variables. Consequently, this study describes the whole market based on graphical information, and a scalable methodology that can be reproduced by investors who want to understand the main trends in the market quickly, and those that look for cryptocurrencies with different financial performance.In our analysis of the 2018 and 2019 for extended period, we found that the market can be typically segmented in few clusters (five or less), and even considering the intersections, the 6 more populations account for 75% of the market. Regarding the associations between the clusters and descriptive features, we find associations between some clusters with volume, market capitalization, and some financial ratios, which could be explored in future research.
Crh proteins catalyze crosslinking of chitin and glucan polymers in fungal cell walls. Here, we show that the BcCrh1 protein from the phytopathogenic fungus Botrytis cinerea acts as a cytoplasmic ...effector and elicitor of plant defense. BcCrh1 is localized in vacuoles and the endoplasmic reticulum during saprophytic growth. However, upon plant infection, the protein accumulates in infection cushions; it is then secreted to the apoplast and translocated into plant cells, where it induces cell death and defense responses. Two regions of 53 and 35 amino acids are sufficient for protein uptake and cell death induction, respectively. BcCrh1 mutant variants that are unable to dimerize lack transglycosylation activity, but are still able to induce plant cell death. Furthermore, Arabidopsis lines expressing the bccrh1 gene exhibit reduced sensitivity to B. cinerea, suggesting a potential use of the BcCrh1 protein in plant immunization against this necrotrophic pathogen.
Purpose
The purpose of this paper is to determine the most influential countries and universities that have contributed to science in the field of industrial marketing research during the period from ...1990 to 2015.
Design/methodology/approach
Bibliometric methodology is adopted, focusing on the most productive and influential countries and universities within this discipline, for the scientific community analyzing journals listed in the Web of Science (WoS) database from 1990 to 2015 and is supplemented by using VOS viewer to graph the existing bibliometric networks for each and every variable.
Findings
Evidence that the USA and UK remain leaders in the investigation of industrial marketing research. Finland stands at the third place, leaving Australia and Germany behind. In reference to the universities, Michigan State University ranks as the leader.
Research limitations/implications
The process of data classification originates from WoS. Moreover, to provide a comprehensive analytical scenario, other factors could have potentially been considered such as the editor’s commitment to leading journals, to partnerships and conferences, as well as other databases.
Originality/value
This paper takes into account alternative variables that have not been previously considered in previous studies, such as universities and countries in which the transcendental contributions to this field have taken place, providing a closer look, which gives rise to further discussions and studies with more detail to the history of this science in the future.
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