Acoustic sequences in non‐human animals: a tutorial review and prospectus

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well‐known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise – let alone understand – the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near‐future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, ‘Analysing vocal sequences in animals’. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial‐style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.     

Kallikrein 5 inhibitors identified through structure based drug design in search for a treatment for Netherton Syndrome

Netherton syndrome (NS) is a rare and debilitating severe autosomal recessive genetic skin disease with high mortality rates particularly in neonates. NS is caused by loss-of-function SPINK5 mutations leading to unregulated kallikrein 5 (KLK5) and kallikrein 7 (KLK7) activity. Furthermore, KLK5 inhibition has been proposed as a potential therapeutic treatment for NS. Identification of potent and selective KLK5 inhibitors would enable further exploration of the disease biology and could ultimately lead to a treatment for NS. This publication describes how fragmentation of known trypsin-like serine protease (TLSP) inhibitors resulted in the identification of a series of phenolic amidine-based KLK5 inhibitors 1. X-ray crystallography was used to find alternatives to the phenol interaction leading to identification of carbonyl analogues such as lactam 13 and benzimidazole 15. These reversible inhibitors, with selectivity over KLK1 (10–100 fold), provided novel starting points for the guided growth towards suitable tool molecules for the exploration of KLK5 biology.     

Unraveling the Nexus: Exploring the Pathways to Combined Resource Use

In response to the unprecedented decline in global natural resource endowments, the so‐called nexus framework is gaining increasing influence on resource management practices. In this research, we approach the resource nexus through the concept of nexus pathways. Nexus pathways are configurations that resource flows follow along supply chains leading to the combined use of two or more resources. Three general types of pathways are identified: direct (on‐site use), dependent (one‐way supply chains), and interdependent (supply‐chain feedbacks). We quantify and compare each pathway by means of multiregional input‐output analysis and structural path analysis, and apply this approach to a comparative case study on the water‐energy nexus (WEN) in the United States and China. Interdependencies or feedbacks are generally thought to be relevant for the WEN, especially between water and energy sectors. Our economy‐wide analysis for both countries indicates, however, that feedbacks neither play an important role in the WEN nor substantially take place between water and energy sectors. The most important feedbacks contribute to less than 1% of total resource use, and these take place mostly between manufacturing sectors. Overall, the studied WEN is mostly driven by dependent pathways and, to a lesser degree, direct resource use. Comparative differences between the two countries are largely explained by differences in economic structure, technology, and resource endowments. Our findings call into question current research and policy focus and suggest greater attention to less complex, but more determining, pathways leading to absolute resource use.     

Interactive Visualization and Industrial Ecology: Applications,Challenges, and Opportunities

The emergence of increasingly complex data in industrial ecology (IE) has caused scholarly interest in interactive visualization (IV). IV allows users to interact with data, aiding in processing and interpreting complex datasets, processes, and simulations. Consequently, IV can help IE practitioners communicate the complexities of their methods and results, shed light on the underlying research assumptions, and enable more transparent monitoring of data quality and error. This can significantly increase the reach and impact of research, promote transparency, reproducibility, and open science, as well as improve the clarity and presentation of IE research. A review of current IV applications reveals that, while data exploration has received some attention among IE practitioners, IV applications in scientific communication are clearly lacking. With the help of a working example, we explore the value of IV, discuss its operationalization, and highlight challenges that the IE community must face during IV uptake. Such challenges include technical and knowledge limitations, limits on user interaction, and implementation strategies. With these challenges in mind, we outline key aspects needed to lift the IE field to the forefront of scientific communication in the coming years. Among these, we draft the basic principles of a “Hub for Interactive Visualization in Industrial Ecology” (HIVE), a point of encounter where IE practitioners could find an array of data visualization tools that are geared toward IE datasets. IV is here to stay, and its inceptive stage presents many opportunities to IE practitioners to shape its operationalization and benefit from early adoption.     

Method for endogenizing capital in the United States Environmentally‐Extended Input‐Output model

Each year businesses, governments, and homeowners in the United States invest around one fifth of gross domestic product into the creation of capital assets such as buildings, machinery, and software to enable production and consumption. Use of capital is typically included to some extent in environmental life cycle assessments of goods and services but is not incorporated into most environmentally extended input‐output (EEIO) models, including the US Environmental Protection Agency's USEEIO. Capital assets are typically created in years prior to their use, so a challenge lies in distributing the impacts of their creation over time. In this work, a highly detailed capital flow matrix approach is followed to distribute the use of fixed capital assets to consuming industries. Data from the US Bureau of Economic Analysis's Fixed Asset Accounts is merged with its Industry Accounts data by the creation of concordance tables. Public highways and streets are partially reallocated to industries operating vehicles. The resulting capital use matrix is later combined into a modified USEEIO. “Housing” is found to be the largest consumer of fixed assets, followed by general government, fossil fuel extraction, and financial industries involved in leasing. Construction, vehicles, and machinery are mostly used by industries in the form of fixed assets. The types of fixed assets used by industries are consistent with expectations: housing is dominated by structures, transport by equipment, and information industries by intellectual property products.