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Piezo-tribo-electric nanogenerator based on BCZT/MCNTs/PDMS piezoelectric composite for compressive energy harvesting
No full textBackground:
This work has developed a novel piezo-tribo-electric nanogenerator (P-TENG) that is capable of converting mechanical energy into electrical energy when operating in compressive mode.
Methods:
An arch-shaped P-TENG device was formed using an optimal piezoelectric polymer composite, which was fabricated using a polydimethylsiloxane (PDMS) matrix that was modified with piezoelectric (Ba0.85Ca0.15) (Ti0.90Zr0.10)O3 (BCZT) ceramic particles and electrically conductive multi-walled carbon nanotubes (MCNTs). A high filler loading of BCZT (40, 50, 60 wt%) and 3 wt% of MCNTs was formed into a 0–3 connectivity composite.
Results:
The P-TENG device containing 50 wt% BCZT exhibited the highest electrical output (VOC ∼ 39.7 V, ISC ∼ 1.9 µA, and maximum power ∼ 157.7 µW), compared to the other composites, when subjected to an alternating compressive load of 500 N at a 1 Hz frequency.
Conclusions:
This research provides new composite formulations for elastomeric-based energy generators that are responsive to low frequency mechanical oscillations
Examining antibiotic use in Kenya: farmers’ knowledge and practices in addressing antibiotic resistance
Get PDFBackground: Antibiotics hold the promise of mitigating the spread of livestock diseases while enhancing productivity. However, there is global concerns surrounding the improper handling and administration of antibiotics, which has led to an alarming rise in antimicrobial resistance (AMR). Kenya is currently listed as an AMR hotspot. This study assesses farmers’ knowledge and practices on antibiotics in livestock production, knowledge on AMR as well as factors influencing farmers’ knowledge of antibiotic safety and resistance, and antibiotics use. Methods: A across-sectional, quantitative survey was employed with 319 farming households in five counties in Kenya. Multivariate regression analysis was used to identify explanatory factors. Results: About 80% of households use antibiotics in their livestock, and 58% administer the antibiotics themselves. The vast majority of farmers buy antibiotics without a prescription. Antibiotics are used for both therapeutic and non-therapeutic purposes, the latter mainly in form of growth promoters and feed enhancers in poultry. The withdrawal periods reported by farmers are shorter than the officially recommended periods. Although the majority of farmers reported risky antibiotic practices, most (76%) were well aware of bacterial AMR. Nineteen of 21 knowledge statements on AMR and safe use of antibiotics were answered correctly by 55–89% of respondents, indicating considerable farmer knowledge on different aspects of antibiotics risk, while certain knowledge gaps remain. Number of livestock owned was the factor most positively influencing farmers’ knowledge on AMR and safe use. Conclusion: Kenya has made notable progress towards creating knowledge and awareness of farming communities on the risks and requirements associated with antibiotic use in livestock. Nonetheless, farmers’ antibiotics practices continue to constitute considerable risk of further AMR development. This shows that knowledge is not enough to ensure fundamental behavioral change. There needs to be an enabling environment driven by (1) effective policy interventions and enforcement to ensure compliance with set guidelines for antibiotic use; (2) research on and deployment of alternatives, such as probiotics, vaccinations and disease prevention measures, (3) continued public awareness raising and education using multiple channels to reach farmers and, (4) strengthened cross-sector, multi-stakeholder collaboration to address the multi-dimensional complexities of AMR
Governing Chinese technologies : TikTok, foreign interference, and technological sovereignty
Get PDFTikTok bans have been presented as one solution to threats to national security, data security, foreign interference, child safety, and foreign espionage. In this article we investigate four countries/regions — Australia, the United Kingdom, the United States, and the European Union — that have banned or attempted to govern TikTok, examining the policy and legal bases for such restrictions. Our analysis is conceptually informed by legal and political narrations of foreign interference and technological sovereignty. We approach this with particular attention to countries with existing intelligence and data sharing agreements (i.e. three members of the Five Eyes alliance and the trilateral AUKUS alliance) and the European Union given its regulatory approach to data protection. This research makes significant and timely contributions to the geopolitics of TikTok and foreign interference in an international context. It informs inconsistencies in regulatory and legal approaches relating to foreign interference and data sovereignty, beyond “China threat” narratives. We argue that the European Union regulation presents an approach that attempts to protect citizens and citizen data rather than attack platforms and governments that challenge Western technological hegemony
Co-designing grounded visualisations of the Food-Water-Energy nexus to enable urban sustainability transformations
Get PDFIn the past few years, the Food-Water-Energy (FWE) Nexus has emerged as a key concept to address the complex relationships and interdependencies between food, water, and energy systems. Cities are an important context for understanding the FWE nexus given their significant footprints and complex socio-ecological systems, but researchers have only recently started to explore an explicit urban perspective on food, water, and energy interrelationships. This paper tackles a particularly significant knowledge gap in this context by introducing an approach to co-design visualisations of the FWE nexus that are understandable and actionable for the various stakeholders involved in urban governance such as citizens, communities, governments, non-governmental and private-sector organisations. Drawing on user-centred design and inspired by the dialogic pedagogy of Paulo Freire, we present and evaluate the co-design process of a FWE nexus visualisation tool for stakeholders engaged with pre-school education in Słupsk, Poland. Our results provide evidence that this co-design process has been effective to developing a new critical consciousness in the participants about how their everyday choices are related to the FWE nexus, enabling them to change perspectives, leading to more sustainable choices. We propose that our co-design process can be used to develop 'grounded visualisations' of the FWE nexus, i.e., visualisations that are grounded in the experiential situations and lived realities of stakeholders, thus offering an effective support for decision-making that could open pathways to sustainability transformations
Polymorphism and structural variety in Sn(II) carboxylate coordination polymers revealed from structure solution of microcrystals
Get PDFThe crystal structures of four coordination polymers constructed from Sn(II) and polydentate carboxylate ligands are reported. All are prepared under hydrothermal conditions in KOH or LiOH solutions (either water or methanol–water) at 130−180 °C and crystallize as small crystals, microns or less in size. Single‐crystal structure solution and refinement are performed using synchrotron X‐ray diffraction for two materials and using 3D electron diffraction (3DED) for the others. Sn2(1,3,5‐BTC)(OH), where 1,3,5‐BTC is benzene‐1,3,5‐tricarboxylate, is a new polymorph of this composition and has a three‐dimensionally connected structure with potential for porosity. Sn(H‐1,3,5‐BTC) retains a partially protonated ligand and has a 1D chain structure bound by hydrogen bonding via ─COOH groups. Sn(H‐1,2,4‐BTC) contains an isomeric ligand, benzene‐1,2,4‐tricarboxylate, and contains inorganic chains in a layered structure held by hydrogen bonding. Sn2(DOBDC), where DOBDC is 2,5‐dioxido‐benzene‐1,4‐dicarboxylate, is a new polymorph for this composition and has a three‐dimensionally connected structure where both carboxylate and oxido groups bind to the tin centers to create a dense network with dimers of tin. In all materials, the Sn centers are found in highly asymmetric coordination, as expected for Sn(II). For all materials phase purity of the bulk is confirmed using powder X‐ray diffraction, thermogravimetric analysis, and infrared spectroscopy
The effect of task-irrelevant objects in spatial contextual cueing
Get PDFDuring visual search, the spatial configuration of the stimuli can be learned when the same displays are presented repeatedly, thereby guiding attention more efficiently to the target location (contextual cueing effect). This study investigated how the presence of a task-irrelevant object influences the contextual cueing effect. Experiment 1 used a standard T/L search task with “old” display configurations presented repeatedly among “new” displays. A green-filled square appeared at unoccupied locations within the search display. The results showed that the typical contextual cueing effect was strongly reduced when a square was added to the display. In Experiment 2, the contextual cueing effect was reinstated by simply including trials where the square could appear at an occupied location (i.e., underneath the search stimuli). Experiment 3 replicated the previous experiment, showing that the restored contextual cueing effect did not depend on whether the square was actually overlapping with a stimulus or not. The final two experiments introduced a display change in the last epoch. The results showed that the square does not only hinder the acquisition of contextual information but also its manifestation. These findings are discussed in terms of an account where effective contextual learning depends on whether the square is perceived as part of the search display or as part of the display background
Adaptive immune receptor repertoire analysis
No full textB cell and T cell receptor repertoires compose the adaptive immune receptor repertoire (AIRR) of an individual. The AIRR is a unique collection of antigen-specific receptors that drives adaptive immune responses, which in turn is imprinted in each individual AIRR. This supports the concept that the AIRR could determine disease outcomes, for example in autoimmunity, infectious disease and cancer. AIRR analysis could therefore assist the diagnosis, prognosis and treatment of human diseases towards personalized medicine. High-throughput sequencing, high-dimensional statistical analysis, computational structural biology and machine learning are currently employed to study the shaping and dynamics of the AIRR as a function of time and antigenic challenges. This Primer provides an overview of concepts and state-of-the-art methods that underlie experimental and computational AIRR analysis and illustrates the diversity of relevant applications. The Primer also addresses some of the outstanding challenges in AIRR analysis, such as sampling, sequencing depth, experimental variations and computational biases, while discussing prospects of future AIRR analysis applications for understanding and predicting adaptive immune responses
Ontology-based scenario generation for automated driving systems verification and validation using rules of the road
Get PDFThe verification and validation (V&V) process for Automated Driving Systems (ADS) has undergone a significant transformation in defining the meaning of safety. Initially rooted in the quantity of miles driven, it has now shifted towards emphasizing the quality of test miles. These test miles must effectively capture the full spectrum of behaviours and operational design domains (ODD) of the ADS. To assess an ADS's compliance with specific rules or requirements, a connection must be established between the rules and the scenarios used for testing. In this paper, we propose a targeted scenario generation methodology aimed at testing ADS against formal rules. Our approach leverages ontologies to represent objects and their relationships in a scenario. The rules, are first formally specified, expressed as horn clauses. We then employ a rule transformation process, along with off-the-shelf reasoning tools, to generate corresponding scenarios. These generated scenarios may then utilized to test the ADS's adherence to the specified rules.
To illustrate the effectiveness of our methodology, we present an application to example rules derived from both the UK Highway Code and the Vienna Conventions. By utilizing our approach, we enhance the precision and rigor of the verification and validation flow for ADS, ensuring improved safety measures during operation
Frequent winners explain apparent skewness preferences in experience-based decisions
No full textDo people’s attitudes toward the (a)symmetry of an outcome distribution affect their choices? Financial investors seek return distributions with frequent small returns but few large ones, consistent with leading models of choice in economics and finance that assume right-skewed preferences. In contrast, many experiments in which decision-makers learn about choice options through experience find the opposite choice tendency, in favor of left-skewed options. To reconcile these seemingly contradicting findings, the present work investigates the effect of skewness on choices in experience-based decisions. Across seven studies, we show that apparent preferences for left-skewed outcome distributions are a consequence of those distributions having a higher value in most direct outcome comparisons, a “frequent-winner effect.” By manipulating which option is the frequent winner, we show that choice tendencies for frequent winners can be obtained even with identical outcome distributions. Moreover, systematic choice tendencies in favor of right- or left-skewed options can be obtained by manipulating which option is experienced as the frequent winner. We also find evidence for an intrinsic preference for right-skewed outcome distributions. The frequent-winner phenomenon is robust to variations in outcome distributions and experimental paradigms. These findings are confirmed by computational analyses in which a reinforcement-learning model capturing frequent winning and intrinsic skewness preferences provides the best account of the data. Our work reconciles conflicting findings of aggregated behavior in financial markets and experiments and highlights the need for theories of decision-making sensitive to joint outcome distributions of the available options