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Television as we knew it is irrevocably changing. Some are gleefully announcing the death of television, others have been less sanguine but insist that television is radically changing underneath our eyes. Several excellent publications have dealt with television’s uncertain condition, but few have taken the specific question of what television’s transformations mean for the discipline of Television Studies as a starting point. The essays collected in this volume aim to fill this void. Two fundamental questions string the various contributions together. First, is television really in crisis or is the present not so extraordinary when revisiting television’s development? Second, should we invent new theoretical concepts or are our old ones still perfectly relevant? To answer such questions the authors in this volume take up diverse case studies, ranging from the academic series Reading Contemporary Television to Flemish Fiction, from nostalgic programming on broadcast television to YouTube, from tell-sell television shows to public television art in the 1980s.

Metabolic engineering has been enabling development of high performance microbial strains for the efficient production of natural and non-natural compounds from renewable non-food biomass. Even though microbial production of various chemicals has successfully been conducted and commercialized, there are still numerous chemicals and materials that await their efficient bio-based production. Aromatic chemicals, which are typically derived from benzene, toluene and xylene in petroleum industry, have been used in large amounts in various industries. Over the last three decades, many metabolically engineered microorganisms have been developed for the bio-based production of aromatic chemicals, many of which are derived from aromatic amino acid pathways. This review highlights the latest metabolic engineering strategies and tools applied to the biosynthesis of aromatic chemicals, many derived from shikimate and aromatic amino acids, including l -phenylalanine, l -tyrosine and l -tryptophan. It is expected that more and more engineered microorganisms capable of efficiently producing aromatic chemicals will be developed toward their industrial-scale production from renewable biomass.

We study algorithms for solving a problem of constructing a text (a long string) from a dictionary (a sequence of small strings). The problem has an application in bioinformatics and has a connection with the sequence assembly method for reconstructing a long DNA sequence from small fragments. Our problem is the construction a string t of length n using strings s1,⋯,sm with possible overlapping. Firstly, we provide a classical (randomized) algorithm with running time On+L+m(logn)2=O~(n+L) where L is the sum of lengths of s1,⋯,sm. Secondly, we provide a quantum algorithm with running time On+logn·(logm+loglogn)·m·L=O~n+m·L. Additionally, we show that the lower bound for a classical (randomized or deterministic) algorithm is Ω(n+L). Thus, our classical algorithm is optimal up to a log factor, and our quantum algorithm shows a speed-up when compared with any classical (randomized or deterministic) algorithm in the case of non-constant length of strings in the dictionary.

For modern radars with high resolutions, an extended target may generate more than one observations. The conventional point target-based tracking method can hardly be applied in such scenarios. Recently, the ET-GM-PHD approach has been presented for tracking these extended targets. The performance of such an approach has been influenced by the following disadvantages. First, it has been formulated under the linear Gaussian assumptions. When targets move with nonlinear models, the tracking performance may be rapidly decreased. Second, it neglects the time associations of the estimated states at different time steps, which makes it very challenging to manage targets for the radar systems. In this paper, we present a labeled ET-GM-PHD approach based on the square root cubature information filter (SRCIF) to solve such problems. To be more specific, we, first, utilize the SCRIF for predicting and updating the GM components of the ET-GM-PHD approach. For decreasing the computational cost, a candidate observation extracting method has been put forward in the GM component updating step. Thus, the ET-GM-PHD approach can be adopted to track extended targets with nonlinear motions. Second, a label-based trajectory constructing method has been proposed. By assigning the GM components with different labels before the GM component predicting step, we can obtain the estimated states with different labels. On this basis, the associations between the estimated states and trajectories can be modeled based on these labels. Thus, we can obtain the states and trajectories of multi extended targets simultaneously. The simulation results prove the effectiveness of our approach.

Combining traditional culture and moral education is particularly important in the Internet era. This study explores the application of conventional culture in moral education and proposes practical strategies for integrating traditional culture into moral education. The study first analyzes the symbiotic pathway between traditional culture and moral education, emphasizing the importance of conventional culture in ecological moral education. Then, by constructing a coupled evaluation index system of conventional culture and moral education and applying the entropy value method and the coupled coordination degree model, it comprehensively evaluated the moral education subsystem in a province from 2008 to 2022. The results show that the province’s honest education subsystem scores improve from 0.1146 to 0.8133, and the coupling coordination degree shows an upward trend. Based on these findings, this study proposes strategies for integrating excellent traditional culture into moral education, including establishing a scientific concept of integration, enhancing teachers, and enriching extracurricular activities, aiming to improve the effectiveness and usefulness of moral education.

Metabolic engineering allows for the rewiring of basic metabolism to overproduce both native and non-native metabolites. Among these biomolecules, nutraceuticals have received considerable interest due to their health-promoting or disease-preventing properties. Likewise, microbial engineering efforts to produce these value-added nutraceuticals overcome traditional limitations of low yield from extractions and complex chemical syntheses. This review covers current strategies of metabolic engineering employed for the production of a few key nutraceuticals with selecting polyunsaturated fatty acids, polyphenolic compounds, carotenoids and non-proteinogenic amino acids as exemplary molecules. We focus on the use of both mono-culture and co-culture strategies to produce these molecules of interest. In each of these cases, metabolic engineering efforts are enabling rapid production of these molecules.

Naturally occurring carotenoids have been isolated and used as colorants, antioxidants, nutrients, etc. in many fields. There is an ever-growing demand for carotenoids production. To comfort this, microbial production of carotenoids is an attractive alternative to current extraction from natural sources. This review summarizes the biosynthetic pathway of carotenoids and progresses in metabolic engineering of various microorganisms for carotenoid production. The advances in synthetic pathway and systems biology lead to many versatile engineering tools available to manipulate microorganisms. In this context, challenges and possible directions are also discussed to provide an insight of microbial engineering for improved production of carotenoids in the future.

This paper is motivated by a methodological interest in how to investigate information infrastructures as an empirical, real-world phenomenon. We argue that research on information infrastructures should not be captive to the prevalent method choice of small-scale and short-term studies. Instead research should address the challenges of empirically studying the heterogeneous, extended and complex phenomena of infrastructuring with an emphasis on the necessarily emerging and open-ended processual qualities of information infrastructures. While existing literature identifies issues that make the study of infrastructuring demanding, few propose ways of addressing these challenges. In this paper we review characteristics of information infrastructures identified in the literature that present challenges for their empirical study. We look to current research in the social sciences, particularly anthropology and science and technology studies (STS) that focus on how to study complex and extended phenomena ethnographically, to provide insight into the study of infrastructuring. Specifically, we reflect on infrastructuring as an object of ethnographic inquiry by building on the notion of “constructing the field.” Recent developments in how to conceptualize the ethnographic field are tied both to longstanding traditions and novel developments in anthropology and STS for studying extended and complex phenomena. Through a discussion of how dimensions of information infrastructures have been addressed practically, methodologically, and theoretically we aim to link the notion of constructing the ethnographic field with views on infrastructuring as a particular kind of object of inquiry. Thus we aim to provide an ethnographically sensitive and methodologically oriented “opening” for an alternative ontology for studying infrastructuring ethnographically.

Introduction to dossierConstructing borders and understanding citizenship: Cross-border societies in the Amazon

We have developed a computational modeling method for analyzing staging biophysical processes with sharp transitions between dynamic regimes and analyze the observed important forms of aggressive invasive processes in models. These models take into account the existence of variants in the evolution of a crisis situation depending on physical and biotic factors. Hazardous invasions of foreign forms of life occur during a biophysical interaction with isolated systems. We model fast changing of stages and alteration of outbreaks and depressions of population waves. Hazardous rapid events investigated in this study appear upon the invasion of a new agent into the existing medium. Invasive processes also depend on the rate of active resistance exerted by the biota as well as on the physical medium factors and the climate. In special conditions, the effect of population outbreak of the spreading undesirable species. Apart from the climatic factor, the response of biotic environment is important. Aggressive invasions often occur as oscillating processes, but waves are transformed upon the adaptation of a foreign organism and the biotic medium. The series of activity peaks decay as a result of adaptation of the autochthonous biota to the invader. We have developed a method for constructing computational scenario models based on a logically extendable hybrid structure of equations. For modeling the evolution of the situation, we propose that the right-hand sides of equations be reconstructed in accordance with the evolution stages of antagonistic biophysical systems. The method for constructing hybrid structures takes into account the stages and delayed adaptation, which is manifested during the evolution and depression of an invasive outbreak. The developed hybrid models have made it possible to consider three actually observed variants of evolution and termination of the extremal phenonon of population outbreak of aggressive species. Invasive scenarios are classified and analyzed in the model from the dynamics of their evolution stages using as an example the situation of invasions in the Caspian Sea and in biocenoses of forest in North America, which often experience rapid defoliation. Small insects, which have many enemies in some special conditions, turn out to be capable of unbelievably fast reproduction; however, a certain time is required for restoring resources. The model scenarios describe series of peaks with decaying activity after the primary outbreak with a transition to a chaotic regime, when the situation of complete disappearance of a hazardous foreign organism from the medium is probable. In the model, two types of bifurcation of attractors are used, which makes it possible to estimate the factors responsible for repeated activity of an invasive population after the depression stage. Climatic factors alone can be insufficient for initiating an aggressive outbreak. Not only new vermin, but also antagonists of main enemies of conventional vermin turn out to be hazardous invaders. An important factor is the invasion of a superparasite. Invaders destroy the stability of regulating mechanisms that sustain the balance and fragile equilibrium. In an organism, the algorithms of action of immune reaction complex sustained by the community of more than 90 types of immune cells are responsible for the resistance to invasion. A retarded response is possible; for example, an acute infection has been transformed into chronic Long COVID. So different epidemic situations with COVID and invasive phenomena cannot be described by a unified model. We propose a different approach based on analysis of similarity of scenarios and analogies. A distinguishing feature of the modeling method is that the properties of phenomena are classified according to the types of their nonlinearity. Only after the establishing the properties of apparent oscillations, it is possible to work out an redetermined structure of equations precisely for modeling the observed type of a biophysical process.