Invited review: Sensor technologies for real-time monitoring of the rumen environment.

Quantifying digestive and fermentative processes within the rumen environment has been the subject of decades of research; however, our existing research methodologies preclude time-sensitive and spatially explicit investigation of this system. To better understand the temporal and spatial dynamics of the rumen environment, real-time and in situ monitoring of various chemical and physical parameters in the rumen through implantable microsensor technologies is a practical solution. Moreover, such sensors could contribute to the next generation of precision livestock farming, provided sufficient wireless data networking and computing systems are incorporated. In this review, various microsensor technologies applicable to real-time metabolic monitoring for ruminants are introduced, including the detection of parameters for rumen metabolism, such as pH, temperature, histamine concentrations, and volatile fatty acid concentrations. The working mechanisms and requirements of the sensors are summarized with respect to the selected target parameters. Lastly, future challenges and perspectives of this research field are discussed.

Invited review: integration of technologies and systems for precision animal agriculture-a case study on precision dairy farming.

Precision livestock farming (PLF) offers a strategic solution to enhance the management capacity of large animal groups, while simultaneously improving profitability, efficiency, and minimizing environmental impacts associated with livestock production systems. Additionally, PLF contributes to optimizing the ability to manage and monitor animal welfare while providing solutions to global grand challenges posed by the growing demand for animal products and ensuring global food security. By enabling a return to the "per animal" approach by harnessing technological advancements, PLF enables cost-effective, individualized care for animals through enhanced monitoring and control capabilities within complex farming systems. Meeting the nutritional requirements of a global population exponentially approaching ten billion people will likely require the density of animal proteins for decades to come. The development and application of digital technologies are critical to facilitate the responsible and sustainable intensification of livestock production over the next several decades to maximize the potential benefits of PLF. Real-time continuous monitoring of each animal is expected to enable more precise and accurate tracking and management of health and well-being. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring auditability in value chains while assuaging concerns associated with labor shortages. Despite notable advances in PLF technology adoption, a number of critical concerns currently limit the viability of these state-of-the-art technologies. The potential benefits of PLF for livestock management systems which are enabled by autonomous continuous monitoring and environmental control can be rapidly enhanced through an Internet of Things approach to monitoring and (where appropriate) closed-loop management. In this paper, we analyze the multilayered network of sensors, actuators, communication, networking, and analytics currently used in PLF, focusing on dairy farming as an illustrative example. We explore the current state-of-the-art, identify key shortcomings, and propose potential solutions to bridge the gap between technology and animal agriculture. Additionally, we examine the potential implications of advancements in communication, robotics, and artificial intelligence on the health, security, and welfare of animals.

Precision technologies are revolutionizing animal agriculture by enhancing the management of animal welfare and productivity. To fully realize the potential benefits of precision livestock farming (PLF), the development and application of digital technologies are needed to facilitate the responsible and sustainable intensification of livestock production over the next several decades. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring audibility in value chains while assuaging concerns associated with labor shortages. In this paper, we analyze the multilayered network of sensors, actuators, communication, and analytics currently in use in PLF. We analyze the various aspects of sensing, communication, networking, and intelligence on the farm leveraging dairy farms as an example system. We also discuss the potential implications of advancements in communication, robotics, and artificial intelligence on the security and welfare of animals.

Real-Time Generation of Hyperbolic Neuronal Spiking Patterns.

Neuronal spikes are referred to as the electric activity of neurons (in terms of voltage) in response to various biological events such as the sodium and calcium ionic current channels in the brain. Currently, both biological models as well as mathematical models of neuronal spiking patterns have been introduced in the literature. However, very little attempt has been made to run these models in real-time. With applications ranging from hardware neuromorphic circuit designs, artificial intelligence (AI) architectures, to deep brain stimulation, real-time generation of these models is of particular interest in the brain-inspired computing/architecture and neuro-modulation/stimulation research communities. This paper proposes the development of a framework for generating the hyperbolic based single neuronal spiking patterns in real-time. Simulation results confirm that the generated spikes resemble the existing models of neuronal spiking patterns, with additional real-time run capability as well as the ability to change the parameters on the fly. Clinical relevance-Real-time models of neuronal spiking patterns have significant clinical relevance with respect to applications of neuromorphic/AI chips for medical image processing/computer vision, as well as clinical neuroscience, neuromodulation and neurostimulation such as deep brain stimulation for modulating the abnormal effects of neurological diseases.

A Review of the Progress of Thin-Film Transistors and Their Technologies for Flexible Electronics.

Flexible electronics enable various technologies to be integrated into daily life and fuel the quests to develop revolutionary applications, such as artificial skins, intelligent textiles, e-skin patches, and on-skin displays. Mechanical characteristics, including the total thickness and the bending radius, are of paramount importance for physically flexible electronics. However, the limitation regarding semiconductor fabrication challenges the mechanical flexibility of thin-film electronics. Thin-Film Transistors (TFTs) are a key component in thin-film electronics that restrict the flexibility of thin-film systems. Here, we provide a brief overview of the trends of the last three decades in the physical flexibility of various semiconducting technologies, including amorphous-silicon, polycrystalline silicon, oxides, carbon nanotubes, and organics. The study demonstrates the trends of the mechanical properties, including the total thickness and the bending radius, and provides a vision for the future of flexible TFTs.

Enhancement of Charge Transport in Polythiophene Semiconducting Polymer by Blending with Graphene Nanoparticles.

This paper describes a study on the charge transport in a composite of liquid-exfoliated graphene nanoparticles (GNPs) and a polythiophene semiconducting polymer. While the former component is highly conducting, although it consists of isolated nanostructures, the latter offers an efficient charge transport path between the individual GNPs within the film, overall yielding enhanced charge transport properties of the resulting bi-component system. The electrical characteristics of the composite layers were investigated by means of measurements of time-of-flight photoconductivity and transconductance in field-effect transistors. In order to analyze both phenomena separately, charge density and charge mobility contributions to the conductivity were singled out. With the increasing GNP concentration, the charge mobility was found to increase, thereby reducing the time spent by the carriers on the polymer chains. In addition, for GNP loading above 0.2 % (wt.), an increase of free charge density was observed that highlights an additional key role played by doping. Variable-range hopping model of a mixed two- and three-dimensional transport is explained using temperature dependence of mobility and free charge density. The temperature variation of free charge density was related to the electron transfer from polythiophene to GNP, with an energy barrier of 24 meV.

Monitoring performance degradation of cerebellar functions using computational neuroscience methods: implications on neurological diseases.

Neurodegeneration is a major cause of human disease. Within the cerebellum, neuronal degeneration and/or dysfunction has been associated with many diseases, including several forms of cerebellar ataxia, since normal cerebellar function is paramount for proper motor coordination, balance, and motor learning. The cerebellum represents a well-established neural circuit. Determining the effects of neuronal loss is of great importance for understanding the fundamental workings of the cerebellum and disease-associated dysfunctions. This paper presents computational modeling of cerebellar function in relation to neurodegeneration either affecting a specific cerebellar cell type, such as granule cells or Purkinje cells, or more generally affecting cerebellar cells and the implications on effects in relation to performance degradation throughout the progression of cell death. The results of the models show that the overall number of cells, as a percentage of the total cell number in the model, of a particular type and, primarily, their proximity to the circuit output, and not the neuronal convergence due to the relative number of cells of a particular type, is the main indicator of the gravity of the functional deficit caused by the degradation of that cell type. Specifically, the greater the percentage loss of neurons of a specific type and the closer proximity of those cells to the deep cerebellar neurons, the greater the deficit caused by the neuronal cell loss. These findings contribute to the understanding of the functional consequences of neurodegeneration and the functional importance of specific connectivity within a neuronal circuit.