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We report the molecular basis of Aspergillus fumigatus oryzin, allergen Asp f 13, or alkaline proteinase ALP1, containing the sequence motif His–Asp–Ser of the subtilisin family, structure, and function at atomic detail. Given the resolution of the data (1.06 Å), we use fragment molecular replacement with ideal polyalanine α-helices to determine the first crystal structure of oryzin. We probe the catalytic serine through formation of an irreversible bond to a small molecule compound, specifically labeling it, describing the amino acid residues performing the catalytic function. Defined by a self-processed pro-peptide, the active site architecture shapes up pocket-like subsites that bind to and unveil the S1′–S4′ substrate binding preferences. We use molecular modeling to dock a model of the pro-peptide in the S1–S4 region and to dock collagen along the active site cleft. Opposite to the face harboring the catalytic serine, the enzyme binds to a calcium ion in a binding site created by backbone flipping. We use thermal unfolding to show that this metal ion provides structural stability. With no known host inhibitor identified thus far, this structure may hasten the progress of developing new therapeutic agents for diseases caused by pathogenic fungi. [ABSTRACT FROM AUTHOR]

We report the molecular basis of Aspergillus fumigatus oryzin, allergen Asp f 13, or alkaline proteinase ALP1, containing the sequence motif His–Asp–Ser of the subtilisin family, structure, and function at atomic detail. Given the resolution of the data (1.06 Å), we use fragment molecular replacement with ideal polyalanine α-helices to determine the first crystal structure of oryzin. We probe the catalytic serine through formation of an irreversible bond to a small molecule compound, specifically labeling it, describing the amino acid residues performing the catalytic function. Defined by a self-processed pro-peptide, the active site architecture shapes up pocket-like subsites that bind to and unveil the S1′–S4′ substrate binding preferences. We use molecular modeling to dock a model of the pro-peptide in the S1–S4 region and to dock collagen along the active site cleft. Opposite to the face harboring the catalytic serine, the enzyme binds to a calcium ion in a binding site created by backbone flipping. We use thermal unfolding to show that this metal ion provides structural stability. With no known host inhibitor identified thus far, this structure may hasten the progress of developing new therapeutic agents for diseases caused by pathogenic fungi. [ABSTRACT FROM AUTHOR]

Research shows that teams comprised of individuals with differing knowledge are increasingly important to enabling innovation in organizations. Beyond diverse connections, research also shows individuals must be familiar with their collaborators' areas of expertise to effectively integrate knowledge. Despite growing recognition of the importance of familiarity for interdisciplinary collaboration, we argue that there is reason to suspect this form of relationship is likely to be particularly rare in organizations. We present an egocentric analysis of collaboration networks in a scientific organization, exploring factors associated with the copresence of interdisciplinary ties alongside familiarity with a collaborator's area of expertise. Our results demonstrate pressures toward similarity of expertise that minimized connections to differing alters. Furthermore, those respondents who had diverse connections tended to be unfamiliar with their distant collaborators' domains. Interaction counteracted this effect but participants reported pressures inhibiting interaction across knowledge boundaries. The findings demonstrate how network forces compound to inhibit what we call "different yet familiar" ties and, by doing so, offer conceptual and practical implications for contemporary organizations. [ABSTRACT FROM AUTHOR]

• The chemometric methods were used to screen out unreliable data. • The FFNN model I(8)-HL(9)-O(1) has been developed to classify the water quality. • The LSTM-MA model was used to classify the water quality over the years 2020 to 2022. • This LSTM-MA model becomes reliable management for the water quality classification. This study has classified and predicted the water quality for the Dong Nai river at different times. The data mining techniques were used to screen out unreliable data. The neural network model FFNN in the form of architecture I(8)-HL(9)-O(1) has been successfully developed to classify the water quality of the Dong Nai river during the period from 2012 to 2019. For this model, the RMSE values for the training, validation, and test sets are equal to 0.0392, 0.0411, and 0.0423, respectively. Also, the MAPE values for those data sets are 1.241, 1.444, and 1.511, respectively. The models ARIMA(0,1,3)(1,1,1), NAR, NAR-MA, LSTM, and LSTM-MA were used to forecast the water quality according to different time series (months) k = 12 and k = 24 at the monitoring points. The LSTM-MA hybrid model provided faster training time and more reliable forecasts than the ARIMA, NAR, NAR-MA, and LSTM models. The RMSE and MAPE values of the LSTM-MA hybrid model for predicting the forecast set are smaller than those from other models. The LSTM-MA hybrid model was used to classify the water quality over the years 2020 to 2022. The water quality classification derived from the LSTM-MA hybrid model in close agreement with the actual monitoring data. This model becomes reliable and useful for the water quality classification of the Dong Nai River. [ABSTRACT FROM AUTHOR]

Balance theory explains how network structural configurations relate to tension in social systems, which are commonly modeled as static undirected signed graphs. We expand this modeling approach by incorporating directionality of edges and considering three levels of analysis for balance assessment: triads, subgroups, and the whole network. For triad-level balance, we develop a new measure by utilizing semicycles that satisfy the condition of transitivity. For subgroup-level balance, we propose measures of cohesiveness (intra-group solidarity) and divisiveness (inter-group antagonism) to capture balance within and among subgroups. For network-level balance, we re-purpose the normalized line index to incorporate directionality and assess balance based on the proportion of edges whose position suits balance. Through comprehensive computational analyses, we quantify, analyze, and compare patterns of social structure in triads, subgroups, and the whole network across a range of social settings. We then apply our multilevel framework to examine balance in temporal and multilayer networks to demonstrates the generalizability of our approach. In most cases, we find relatively high balance across the three levels; providing another confirmation of balance theory. We also deliver empirical evidence for the argument that balance at different levels is not the same social phenomenon measured at different scales, but represents different properties (triadic balance, internal cohesion and external division of subgroups, and overall network polarization), and should therefore be evaluated independently from one another. We propose a comprehensive yet parsimonious approach to address this need. [ABSTRACT FROM AUTHOR]

Although structuration theory (ST) has endured a considerable influence in communication research across various domains, there remains a paucity of quantitative empirical research using ST as a viable framework. The purpose of this article is to develop an adapted structurational framework to explain the emergence of communication networks. The adapted framework distinguishes between relational states/events and internal/external structural rules. For analysis, we introduce multipanel relational event modeling, a technique using processual inference that can empirically demonstrate the recursive nature of system and structure. As an introductory example of both the framework and method, we examined communication, using cell-phone data, of students living in the same dormitory from September 2008 through February 2009. Our results demonstrated how different structures (i.e., perceived social relations and internal/external structural rules) are reproduced and transformed over time. Our research has implications for communication research dealing with recursivity, event-driven network analysis, the changing nature of the phone call, and the promise of computational communication science. [ABSTRACT FROM AUTHOR]