Indoor microbiome, environmental characteristics and asthma among junior high school students in Johor Bahru, Malaysia. (arXiv:1911.06946v1 [q-bio.GN])

Indoor microbial diversity and composition are suggested to affect the prevalence and severity of asthma. In this study, we collected floor dust and environmental characteristics from 21 classrooms, and health data related to asthma symptoms from 309 students, in junior high schools in Johor Bahru, Malaysia. Bacterial and fungal composition was characterized by sequencing 16s…

Highly Sensitive and Label-free Digital Detection of Whole Cell E. coli with Interferometric Reflectance Imaging. (arXiv:1911.06950v1 [q-bio.BM])

Bacterial infectious diseases are a major threat to human health. Timely and sensitive pathogenic bacteria detection is crucial in identifying the bacterial contaminations and preventing the spread of infectious diseases. Due to limitations of conventional bacteria detection techniques there have been concerted research efforts towards development of new biosensors. Biosensors offering label free, whole bacteria…

Three cooperative mechanisms required for recovery after brain damage. (arXiv:1911.07012v1 [q-bio.NC])

Stroke is one of the main causes of human disabilities. Experimental observations indicate that several mechanisms are activated during the recovery of functional activity after a stroke. Here we unveil how the brain recovers by explaining the role played by three mechanisms: Plastic adaptation, hyperexcitability and synaptogenesis. We consider two different damages in a neural…

X-ray Multimodal Intrinsic-Speckle-Tracking. (arXiv:1911.06814v1 [eess.IV])

We develop X-ray Multimodal Intrinsic-Speckle-Tracking (MIST), a form of X-ray speckle-tracking that is able to recover both the refractive index decrement and the small-angle X-ray scattering (SAXS) signal of a phase object. MIST is based on combining a Fokker-Planck description of paraxial X-ray optics, with an optical-flow formalism for X-ray speckle-tracking. Only two images need…

Transfer Learning of fMRI Dynamics. (arXiv:1911.06813v1 [eess.IV])

As a mental disorder progresses, it may affect brain structure, but brain function expressed in brain dynamics is affected much earlier. Capturing the moment when brain dynamics express the disorder is crucial for early diagnosis. The traditional approach to this problem via training classifiers either proceeds from handcrafted features or requires large datasets to combat…

Multireference electron correlation methods: Journeys along potential energy surfaces. (arXiv:1911.06836v1 [physics.chem-ph])

Multireference electron correlation methods describe static and dynamical electron correlation in a balanced way, and therefore, can yield accurate and predictive results even when single-reference methods or multiconfigurational self-consistent field (MCSCF) theory fails. One of their most prominent applications in quantum chemistry is the exploration of potential energy surfaces (PES). This includes the optimization of…

Performance assessment of the 2$\gamma$ positronium imaging with the total-body PET scanners. (arXiv:1911.06841v1 [physics.ins-det])

In living organisms the positron-electron annihilation (occurring during the PET imaging) proceeds in about 30% via creation of a metastable ortho-positronium atom. In the tissue, due to the pick-off and conversion processes, over 98% of ortho-positronia annihilate into two 511~keV photons. In this article we assess the feasibility for reconstruction of the mean ortho-positronium lifetime…

Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning. (arXiv:1911.06832v1 [cs.LG])

Humans and animals are capable of quickly learning new behaviours to solve new tasks. Yet, we often forget that they also rely on a highly specialized morphology that co-adapted with motor control throughout thousands of years. Although compelling, the idea of co-adapting morphology and behaviours in robots is often unfeasible because of the long manufacturing…

Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient. (arXiv:1911.06833v1 [cs.LG])

Model-free reinforcement learning algorithms such as Deep Deterministic Policy Gradient (DDPG) often require additional exploration strategies, especially if the actor is of deterministic nature. This work evaluates the use of model-based trajectory optimization methods used for exploration in Deep Deterministic Policy Gradient when trained on a latent image embedding. In addition, an extension of DDPG…