Miracle-dz/UniFAR-FTUs huggingface dataset:
‘Any place to raise children is a good place’: children, housing and neighbourhoods in inner Newcastle, Australia

Neighbourhoods are important spaces of interaction for children. This paper explores the perceptions of residents from seven suburbs in the inner area of Newcastle, Australia concerning what makes a good neighbourhood for children. Key factors identified by residents include the types of dwellings found in the neighbourhood (with detached houses being seen as preferable for children) and the quality of neighbourhood resources. Another important feature was social interactions within the neighbourhood, including interactions between children and adults and interactions between groups of children. The paper examines how different features of neighbourhoods interact to create adult perceptions about whether a neighbourhood is appropriate for children. The paper also points to the ways that children are seen to actively produce the neighbourhood in which they live.
Real-time pedestrian detection and tracking on customized hardware

Real-time pedestrian detection and tracking are vital to many applications, such as the interaction between drones and human. However, the high complexity of Convolutional Neural Network (CNN) makes them rely on powerful servers, thus is hard for mobile platforms like drones. In this paper, we propose a CNN-based real-time pedestrian detection and tracking system, which can achieve 14.7 fps detection and 200 fps tracking with only 3W.
Perceptions About Advance Directives by Nurses in a Community Hospital

Despite the legal mandate for hospitals to comply with the Patient Self-Determination Act and recommendations by the American Nurses’ Association for nurses to advocate for the participation of patients in end-of-life decisions, nurses’ compliance has been less than enthusiastic. This study used an exploratory descriptive design and a 10-item self-reported questionnaire, which included both multiple-choice and open-ended questions. This study examined nurses’ knowledge and comfort with the implementation of the Patient Self-Determination Act. An analysis of this research shows that two major themes emerged: a need for more education involving advance directives and a desire to have other healthcare workers involved in informing patients about advance directives.
Multiple Molecular Subtypes of Triple-Negative Breast Cancer Critically Rely on Androgen Receptor and Respond to Enzalutamide In Vivo

Triple-negative breast cancer (TNBC) has the lowest 5-year survival rate of invasive breast carcinomas, and currently there are no approved targeted therapies for this aggressive form of the disease. The androgen receptor (AR) is expressed in up to one third of TNBC and we find that all AR+ TNBC primary tumors tested display nuclear localization of AR, indicative of transcriptionally active receptors. While AR is most abundant in the “luminal AR (LAR)” molecular subtype of TNBC, here, for the first time, we use both the new-generation anti-androgen enzalutamide and AR knockdown to demonstrate that the other non-LAR molecular subtypes of TNBC are critically dependent on AR protein. Indeed, AR inhibition significantly reduces baseline proliferation, anchorage-independent growth, migration, and invasion and increases apoptosis in four TNBC lines (SUM159PT, HCC1806, BT549, and MDA-MB-231), representing three non-LAR TNBC molecular subtypes (mesenchymal-like, mesenchymal stem–like, and basal-like 2). In vivo, enzalutamide significantly decreases viability of SUM159PT and HCC1806 xenografts. Furthermore, mechanistic analysis reveals that AR activation upregulates secretion of the EGFR ligand amphiregulin (AREG), an effect abrogated by enzalutamide in vitro and in vivo. Exogenous AREG partially rescues the effects of AR knockdown on proliferation, migration, and invasion, demonstrating that upregulation of AREG is one mechanism by which AR influences tumorigenicity. Together, our findings indicate that non-LAR subtypes of TNBC are AR dependent and, moreover, that enzalutamide is a promising targeted therapy for multiple molecular subtypes of AR+ TNBC. Mol Cancer Ther; 14(3); 769–78. ©2015 AACR.
Exploratory experimentation and taxonomy of experimentation

Transformation of the philosophy of science during the last three decades is largely based on the philosophers’ insights in the experimental side of science. Central issues in this new field, such as classification of basic elements and types of experimentation, are still developing. Subject of this work will be one of these types, Steinle’s „exploratory experimentation“ (EE), and its place in taxonomy of experimentation. After presenting an array of historical cases of experimentation, I analyze Elliott’s systematization of EE subtypes. I will claim that it does not represent development of Steinle’s ideas, although it can be used to improve taxonomy of experimentation in general. Special attention will be dedicated to the development of this taxonomy and understanding forms of experimentation not focused on theory testing - specifically EE.
Improving the Modifiability of the Architecture of Business Applications

In the current rapidly changing business environment, organizations must keep on changing their business applications to maintain their competitive edges. Therefore, the modifiability of a business application is critical to the success of organizations. Software architecture plays an important role in ensuring a desired modifiability of business applications. However, few approaches exist to automatically assess and improve the modifiability of software architectures. Generally speaking, existing approaches rely on software architects to design software architecture based on their experience and knowledge. In this paper, we build on our prior work on automatic generation of software architectures from business processes and propose a collection of model transformation rules to automatically improve the modifiability of software architectures. We extend a set of existing product metrics to assess the modifiability impact of the proposed model transformation rules and guide the quality improvement process. Eventually, we can generate software architecture with desired modifiability from business processes. We conduct a case study to illustrate the effectiveness of our transformation rules.
Hypertonic saline releases the attached small intestinal cystic fibrosis mucus

Hypertonic saline inhalation has become a cornerstone in the treatment of cystic fibrosis (CF), but its effect on CF mucus is still not understood. In CF, mucus stagnates in the airways, causing mucus plugging, and forming a substrate for bacterial invasion. Using horizontal Ussing‐type chambers to allow easy access to the tissue, we have recently shown that the small intestinal mucus of CF mice is attached to the epithelium and not freely movable as opposed to normal mucus, thus pointing to a similarity between the CF mucus in the ileum and airways. In the same type of system, we investigated how hypertonic saline affects mucus thickness, attachment and penetrability to fluorescent beads the size of bacteria in ileal explants from the cystic fibrosis transmembrane conductance regulator mutant (ΔF508) mouse, in order to characterize how this common therapy affects mucus properties. Hypertonic saline (1.75–5%) detached the mucus from the epithelium, but the mucus remained impenetrable to beads the size of bacteria. This approach might be used to test other mucolytic interventions in CF.
Self-adaptive focusing of evolutionary effort in hierarchical genetic programming

In an attempt to address the scaling up of genetic programming to handle complex problems, we have proposed a hierarchical approach in which programs are formed from independently evolved code fragments, each of which is responsible for handling a subset of the test input cases. Although this approach offers substantial performance advantages in comparison to more conventional systems, the programs it evolves exhibit some undesirable properties for certain problem domains. We therefore propose the introduction of a self-adaptive mechanism that allows the system dynamically to focus evolutionary effort on the program components most in need. Experimentation reveals that not only does this technique lead to better-behaved programs, it also gives rise to further significant performance improvements.
Experimental studies of evolution in guppies: a model for understanding the evolutionary consequences of predator removal in natural communities

Guppies (Poecilia reticulata) in Trinidadian streams are found with a diversity of predators in the lower reaches of streams, but few predators in the headwaters. These differences have caused the adaptive evolution of guppy behaviour, morphology, male colouration and life history. Waterfalls often serve as barriers to the upstream distribution of predators and/or guppies. Such discontinuities make it possible to treat streams like giant test tubes by introducing guppies or predators to small segments of streams from which they were previously excluded. Such experiments enable us to document how fast evolution can occur and the fine spatial scales over which adaptation is possible. They also demonstrate that the role predators play in structuring this ecosystem resembles many others studied from a more purely ecological perspective; in these streams, as elsewhere, predators depress the numbers of individuals in prey species which in turn reduces the effects of the prey species on other trophic levels and hence the structure of the ecosystem. A focus on predators is important in conservation biology because predators are often the organisms that are most susceptible to local extinction. Their selective loss occurs because large predators have been deliberately exterminated and/or are more susceptible to environmental disturbances. Furthermore, we will argue that predator re‐introductions might be destabilizing if, in the absence of predators, their prey have evolved in a fashion that makes them highly susceptible to predation, even after time intervals as short as 50–100 years. A better understanding of the evolutionary impacts of top predators will be critical goal for the policy and practice of large carnivore restoration in the future.
Worldsens: a fast and accurate development framework for sensor network applications

In this article, we present Worldsens, a fast and accurate development framework for sensor network applications. World-sens offers an integrated platform for the design, development, performance evaluation and profiling of applications. It relies on two simulators, WSNet and WSim, which are used throughout the application design and implementation, from the high level design choices to the implementation validation. WSNet is a modular event-driven wireless network simulator while WSim is a full platform hardware simulator which takes the target binary code as input and uses instruction cycles as time reference. WSNet and WSim can be used in conjunction to offer a distributed simulation of sensor networks with instruction and radio byte accuracy.
Randomness as a resource for design 1

1 With apologies to Bill Gaver [11]. ABSTRACT Randomness is being harnessed in the design of some interactive systems. This is observed in random blogs, random web searching, and in particular Apple’s iPod Shuffle. Yet the role of randomness in design of interactive systems in not well understood. This paper reports on an empirical study examining the influence of randomness on the user experience of music listening. 113 instances of self-reporting were collected and analysed according to four themes: listening mode, content organisation, activities during listening, and affective outcomes. The analysis provides insights into how randomness is used to engender certain affective responses (such as feeling refreshed) by using various constraining techniques (such as playlists) whilst engaging in everyday activities (such as driving a car). The paper argues that randomness can be used as an innovative design resource for supporting rich and novel user experiences.
Smarter home networks with simple gateways

Users demand smarter home networks that conveniently provide networking features. Previous attempts focus on pushing more features into the gateways and making them smarter. Home gateways, however, have limited resources and cannot accommodate resource-demanding features. In this paper, in contrast, we delegate most gateway functionalities to a shared, consolidated control platform, and keep the gateway as simple as possible. Using this framework, we are not restricted by resource limitations of home gateways and thus are able to provide services such as device discovery or troubleshooting with less effort and better quality.
Preparation and Characterization of an Antibody Antagonist That Targets the Porcine Growth Hormone Receptor

A series of antagonists specifically targeting growth hormone receptors (GHR) in different species, such as humans, rats, bovines, and mice, have been designed; however, there are currently no antagonists that target the porcine growth hormone (GH). Therefore, in this study, we developed and characterized a porcine GHR (pGHR) antibody antagonist (denoted by AN98) via the hybridoma technique. The results from enzyme-linked immunosorbent assay, fluorescence activated cell sorter, indirect immunoinfluscent assay, and competitive receptor binding analysis showed that AN98 could specifically recognize pGHR, and further experiments indicated that AN98 could effectively inhibit pGH-induced signalling in CHO-pGHR cells and porcine hepatocytes. In addition, AN98 also inhibited GH-induced insulin-like growth factor-1 (IGF-1) secretion in porcine hepatocytes. In summary, these findings indicated that AN98, as a pGHR-specific antagonist, has potential applications in pGH-pGHR-related research on domestic pigs.
Surface Layer Analysis of a 28Si-Enriched Sphere Both in Vacuum and in Air by Ellipsometry

For a new definition of the kilogram, surface analysis of Si spheres is essential to determine the Avogadro constant using the X-ray crystal density method. In this paper, to investigate the surface characteristics of Si spheres both in vacuum and in air, a new spectroscopic ellipsometer having a vacuum chamber with an automatic sphere rotation system was developed, using which the thickness of the SiO2 layer on the surface of a 28Si-enriched sphere was determined based on a four-layer model. The obtained oxide layer (OL) thickness was in agreement with that obtained by X-ray photoelectron spectroscopy within their uncertainties. The OL thickness determined in vacuum was larger than that in air by 0.24 nm. This difference was examined by considering the physical properties of the constituents of the four-layer model.
Data exchange: query answering for incomplete data sources

Data exchange is the problem of transforming data structured under a schema, called the source schema, into data structured under another schema, called the target schema. Existing work on data exchange considers settings where the source instance does not contain incomplete information. In this paper we study semantics and address algorithmic issues for data exchange settings where the source instance may contain incomplete data. We investigate the query answering problem in such data exchange settings. First we give two different meaningful semantics to certain answers: One via the certain answers in the corresponding complete data exchange problems and the other via the set of all solutions of the corresponding complete data exchange problems. We use the chase to compute a universal instance which is materialized over the target schema and is used to compute the certain answers to unions of conjunctive queries. We prove that computing certain answers (under both semantics) for unions of conjunctive queries can be done in polynomial time when the schema mapping contains constraints that consist of a weakly acyclic set of tuple-generating dependencies and equality-generating dependencies.
Effectively extracting rules from trained neural networks based on the characteristics of the classification hypersurfaces

The lack of efficient heuristic information is the fundamental reason that causes the low effectiveness of currently used approaches for extracting symbolic rules from trained feedforward neural networks. In this paper, a new measurement method of the classification power of attributes on the basis of the characteristics of the classification hypersurfaces is proposed, which is suitable for both continuous attributes and discrete attributes. Based on this new measurement method, a new approach for rule extraction from trained neural networks and classification problems with continuous attributes is proposed. A new method to adjust the complexity of neural network models based on the output range adjustment is also presented. The performance of the new approach is demonstrated by several computing cases. The results of the experiments prove that the approach proposed can improve the validity of the extracted rules remarkably compared with other rule extracting approaches, especially for the complicated classification problems.
Minimizing Delay for Multicast-Streaming in Wireless Networks with Network Coding

Network coding is a method that promises to achieve the min-cut capacity in multicasts. However, pushing towards this gain in throughput comes with two sacrifices. Delay suffers as the decoding procedure requires buffering and is performed in batches of coded packets, and unfairness prevails in terms of delay increases between receivers with worse channel conditions and those with better channel conditions. In this paper, we focus on optimizing the delay performance in reliably multicasting a data stream to a set of one-hop receivers from the receiver perspective. We analyze the system based on queueing theory using semi-Markov chains from both the system-wide and receiver perspectives. We find that the average delay per received packet at the receivers' end can be minimized by appropriate scheduling of data packets and appropriate size of the coding buffer, which depends on the rate of incoming data stream and capacities of the receivers. To circumvent unduly computational complexities, we design a heuristic scheme which can achieve significant performance gain when compared to an existing method. Our scheme readily adapts the coding size to the dynamics of the system, and schedules data packets to be coded via some strict priority measure for optimized delay performance. We show through extensive simulations that our scheme gives low average delay at high streaming rates and narrows the performance gap between receivers with bad and good channel conditions.
A New Approach using Machine Learning and Data Fusion Techniques for Solving Hard Combinatorial Optimization Problems

We investigate the possibility of using kernel clustering and data fusion techniques for solving hard combinatorial optimization problems. The proposed general paradigm aims at incorporating unsupervised kernel methods into population-based heuristics, which rely on spatial fusion of solutions, in order to learn the solution clusters from the search history. This form of extracted knowledge guides the heuristic to detect automatically promising regions of solutions. The proposed algorithm derived from this paradigm is an extension of the classical scatter search and can automatically learn during the search process by exploiting the history of solutions found. Preliminary results, with an application to the well-known vehicle routing problem (VRP) show the great interest of such paradigm and can effectively find near-optimal solutions for large problem instances.
The Effects of Emotionality of Languages on Evolution of Cultures

Abstract- Abstract-Languages convey emotional as well as conceptual information. Conceptual contents of languages mostly reside in words and their semantic meanings. Emotional contents of languages mostly reside in language prosody (sounds). Conceptual contents could be borrowed among languages. Emotional contents are significantly determined by grammar, and cannot be easily borrowed. Conceptual and emotional mechanisms of languages are considered along with their functions in the mind and cultural evolution. Neural mechanisms are suggested as well as their mathematical models. These include neural modelling fields, dynamic logic, the knowledge instinct, the language instinct, and the dual model connecting language and cognition. Mathematical results are related to cognitive science, linguistics, and psychology. We consider an essential contradiction in human evolution: while evolving from animal vocalizations language evolution has required reduced emotionality. Yet, a language without emotions contains just “empty” sounds, disconnected from sensory-motor experience and “irrelevant to life”. Too “low” emotionality makes languages “irrelevant”, too “high” emotionality makes languages inflexible for acquiring new knowledge. We suggest approaches to quantifying these quoted, difficult to define notions. Experimental evidence and theoretical arguments are discussed. Approximate equations for evolution of human minds and cultures are derived. Their solutions identify just few types of possible cultures and language emotionalities leading to these cultures. We consider evidence and testable predictions. The proposed emotional version of Sapir-Whorf hypothesis suggests that differences in language emotionalities influence differences among cultures no less than conceptual differences. We discuss future research directions.
Realistic protein–protein association rates from a simple diffusional model neglecting long‐range interactions, free energy barriers, and landscape ruggedness

We develop a simple but rigorous model of protein–protein association kinetics based on diffusional association on free energy landscapes obtained by sampling configurations within and surrounding the native complex binding funnels. Guided by results obtained on exactly solvable model problems, we transform the problem of diffusion in a potential into free diffusion in the presence of an absorbing zone spanning the entrance to the binding funnel. The free diffusion problem is solved using a recently derived analytic expression for the rate of association of asymmetrically oriented molecules. Despite the required high steric specificity and the absence of long‐range attractive interactions, the computed rates are typically on the order of 104–106 M−1 sec−1, several orders of magnitude higher than rates obtained using a purely probabilistic model in which the association rate for free diffusion of uniformly reactive molecules is multiplied by the probability of a correct alignment of the two partners in a random collision. As the association rates of many protein–protein complexes are also in the 105–106 M−1 sec−1 range, our results suggest that free energy barriers arising from desolvation and/or side‐chain freezing during complex formation or increased ruggedness within the binding funnel, which are completely neglected in our simple diffusional model, do not contribute significantly to the dynamics of protein–protein association. The transparent physical interpretation of our approach that computes association rates directly from the size and geometry of protein–protein binding funnels makes it a useful complement to Brownian dynamics simulations.