Miracle-dz/UniFAR-FTUs huggingface dataset:
Bicistronic Expression of a High-Performance Calcium Indicator and Opsin for All-Optical Stimulation and Imaging at Cellular Resolution

Abstract State-of-the-art all-optical systems promise unprecedented access to neural activity in vivo, using multiphoton optogenetics to allow simultaneous imaging and control of activity in selected neurons at cellular resolution. However, to achieve wide use of all-optical stimulation and imaging, simple strategies are needed to robustly and stably express opsins and indicators in the same cells. Here, we describe a bicistronic adeno-associated virus (AAV) that expresses both the fast and bright calcium indicator jGCaMP8s, and a soma-targeted (st) and two-photon-activatable opsin, ChrimsonR. With this method, stChrimsonR stimulation with two-photon holography in the visual cortex of mice drives robust spiking in targeted cells, and neural responses to visual sensory stimuli and spontaneous activity are strong and stable. Cells expressing this bicistronic construct show responses to both photostimulation and visual stimulation that are similar to responses measured from cells expressing the same opsin and indicator via separate viruses. This approach is a simple and robust way to prepare neurons in vivo for two-photon holography and imaging.
Maximum entropy analysis of dispersed seismic signals

Conventional moving-window analyzers based on Fourier transforms sometimes lack the resolution required to separate each of the modes in a seismic wave-guide. It is possible to enhance the resolution of a moving-window analyzer by using a maximum entropy power spectral estimator to approximate the spectrum of each windowed segment of a trace. Barrodale and Erickson have developed a suitable maximum entropy algorithm which can also be applied to estimating the parameters required in the fast recompression of in-seam seismic arrivals.The Barrodale-Erickson maximum entropy algorithm appears to need a sample rate of approximately ten times the Nyquist rate in order to generate meaningful maximum entropy spectra. The required increase can be achieved in the laboratory by applying an accurate interpolator to field records. Noise captures the maximum entropy spectrum if the input signal-to-noise ratio falls much below 10 dB. Use of a maximum entropy spectral analyzer aids in both identifying modes in a waveguide system and estimating the group velocity-frequency characteristic parameter.
Radiative cooling efficiencies and predicted spectra of species of the IO plasma torus

Calculations of the physical condition of the Io plasma torus have been made based on the recent Voyager EUV observations. The calculations represent an assumed thin plasma collisional ionization equilibrium among the states within each species. The observations of the torus are all consistent with this condition. The major energy loss mechanism is radiative cooling in discrete transitions. Calculations of radiative cooling efficiencies of the identified species leads to an estimated energy loss rate of at least 2.5 x 10/sup 12/ watts. The mean electron temperature and density of the plasma are estimated to be T=10/sup 5/ K and n/sub e/> or =2100 cm/sup -/u3. The estimated number densities of S III, S IV, and O III are roughly 95, 80, and 190--740 cm/sup -3/. Upper limits have been placed on a number of other species based on the first published Voyager EUV spectrum of the torus. The assumption that energy is supplied to the torus through injection of neutral particles from Io leads to the conclusion that ion loss rates are controlled by diffusion, and relative species abundances consequently are not controlled by collisional ionization equilibrium. However, the ionization equilibrium calculations do apply to the states within a givenmore » species. « less
Harnessing enzyme cofactors and plant metabolism: an essential partnership.

Cofactors are fundamental to the catalytic activity of enzymes. Additionally, because plants are a critical source of several cofactors (i.e., including their vitamin precursors) within the context of human nutrition, there have been several studies aiming to understand the metabolism of coenzymes and vitamins in plants in detail. For example, compelling evidence has been brought forth regarding the role of cofactors in plants; specifically, it is becoming increasingly clear that an adequate supply of cofactors in plants directly affects their development, metabolism, and stress responses. Here, we review the state of the art knowledge on the significance of coenzymes and their precursors with regards to general plant physiology and discuss the emerging functions attributed to them. Furthermore, we discuss how improving our understanding of the complex relationship between cofactors and plant metabolism is a promising tool for crop improvement.
Evidence and potential drivers of neglected parasitic helminth and protist infections among a small preliminary sample of children from rural Mississippi

Intestinal infections with helminths (parasitic worms) and protists (single‐celled eukaryotes) may be neglected health issues in low‐resource communities across the United States. Because they predominantly infect school‐aged children and can lead to nutritional deficiencies and developmental delays, these infections can affect lifelong health. More research is needed to understand the prevalence and risk factors of these parasitic infections in the United States.
De Novo Generation of Pulmonary Ionocytes from Normal and Cystic Fibrosis Human Induced Pluripotent Stem Cells

(aEb7 integrin) signaling in tissue-resident lymphocytes. Am J Physiol Cell Physiol 2022;323:C1161–C1167. 9. Djenidi F, Adam J, Goubar A, Durgeau A, Meurice G, de Montpr eville V, et al. CD8CD103 tumor-infiltrating lymphocytes are tumor-specific tissue-resident memory T cells and a prognostic factor for survival in lung cancer patients. J Immunol 2015;194:3475–3486. 10. Selman M, Pardo A, Barrera L, Estrada A, Watson SR, Wilson K, et al. Gene expression profiles distinguish idiopathic pulmonary fibrosis from hypersensitivity pneumonitis. Am J Respir Crit Care Med 2006;173: 188–198. 11. Richmond JM, Strassner JP, Zapata L Jr, Garg M, Riding RL, Refat MA, et al. Antibody blockade of IL-15 signaling has the potential to durably reverse vitiligo. Sci Transl Med 2018;10:eaam7710.
Clinical Reasoning: Acute Monocular Vision Loss in a Patient With Ipsilateral Extracranial Chronic Internal Carotid Artery Occlusion

We report the case of a middle-aged man who presented with acute painless monocular vision loss. His medical history was remarkable for chronic total occlusion of the ipsilateral internal carotid artery (ICA) and a recent carotid endarterectomy (CEA) on the contralateral ICA. In a stepwise multidisciplinary approach assessment, we review the differential diagnosis of acute vision loss and investigate how the patient's intracranial and extracranial hemodynamic reorganization after chronic ICA occlusion may affect the clinical reasoning. Early complications of CEA and the differential diagnosis of new-onset anisocoria are also discussed.
Industry Adoption of Organoids and Organs‐on‐Chip Technology: Toward a Paradox of Choice

During the last decade, organoid and organs‐on‐chip technologies have significantly enhanced the ability to model human biology in vitro. For the pharmaceutical industry, this represents an opportunity to augment, or possibly replace, traditional preclinical animal studies with more clinically predictive tools. In the last few years, the marketplace for new human model systems has expanded rapidly. While pharma companies welcome the breadth of new options, ample choice can be paralyzing. Even for experts from the model developer community who are now filling the ranks in the industry, the pairing of the right model for a specific, fit‐for‐purpose biological question can be daunting. As a community, the adoption of these models can be hastened in the industry by publishing high dimensional datasets (e.g., multiomic, imaging, functional, etc.) on existing model systems, termed model‐omics, and storing them in publicly accessible databases. This action will allow for quick cross‐model comparisons and provide a sought‐after rationale for either routine or fit‐for‐purpose use of organoids or organs‐on‐chip during drug development.
A Smartphone Intervention to Promote a Sustainable Healthy Diet: Protocol for a Pilot Study

Background Changing current dietary patterns into sustainable healthy diets (ie, healthy diets with low environmental impact and socioeconomic fairness) is urgent. So far, few eating behavior change interventions have addressed all the dimensions of sustainable healthy diets at once and used cutting-edge methods from the field of digital health behavior change. Objective The primary objectives of this pilot study were to assess the feasibility and effectiveness of an individual behavior change intervention toward the adoption of a more environmentally sustainable healthy diet as a whole and changes in specific relevant food groups, food waste, and obtaining food from fair sources. The secondary objectives included the identification of mechanisms of action that potentially mediate the effect of the intervention on behaviors, identification of potential spillover effects and covariations among different food outcomes, and identification of the role of socioeconomic status in behavior changes. Methods We will run a series of ABA n-of-1 trials over a year, with the first A phase corresponding to a 2-week baseline evaluation, the B phase to a 22-week intervention, and the second A phase to a 24-week postintervention follow-up. We plan to enroll 21 participants from low, middle, and high socioeconomic statuses, with 7 from each socioeconomic group. The intervention will involve sending text messages and providing brief individualized web-based feedback sessions based on regular app-based assessments of eating behavior. The text messages will contain brief educational messages on human health and the environmental and socioeconomic effects of dietary choices; motivational messages to encourage the adoption of sustainable healthy diets by participants, providing tips to achieve their own behavioral goals; or links to recipes. Both quantitative and qualitative data will be collected. Quantitative data (eg, on eating behaviors and motivation) will be collected through self-reported questionnaires on several weekly bursts spread through the study. Qualitative data will be collected through 3 individual semistructured interviews before the intervention period, at the end of the intervention period, and at the end of the study. Analyses will be performed at both the individual and group levels depending on the outcome and objective. Results The first participants were recruited in October 2022. The final results are expected by October 2023. Conclusions The results of this pilot study will be useful for designing future larger interventions on individual behavior change for sustainable healthy diets. International Registered Report Identifier (IRRID) PRR1-10.2196/41443
Climate Simulations with a Spectral, semi-Lagrangian Model with Linear Grids

ABSTRACT Semi-Lagrangian, semi-implicit, spectral transform atmospheric models do not require conventional quadratic unaliased Gaussian grids because advection is not expressed as an Eulerian quadratic product in their formulation. The conventional T42 quadratically unaliased grid with 128 (64) points in longitude (latitude) supports a T63 spectral truncation, and similarly for other resolutions. We refer to these types of truncation/grid combinations as aliased or linear grids, since they can be considered as being aliased for quadratic products or unaliased for linear terms. In this paper, climate simulations based on linear grids are compared with ones based on quadratic unaliased grids. It is shown that for spectral resolutions above T42, the spectral truncation, rather than the transform grid on which the physical parametrizations are calculated, dominates the accuracy of simulations. Thus the linear grid provides a 50 percent increase in resolution of both horizontal dimensions at a negligible addit.
The third barrier to transgenerational inheritance in animals: somatic epigenetic resetting

After early controversy, it is now increasingly clear that acquired responses to environmental factors may perpetuate across multiple generations—a phenomenon termed transgenerational epigenetic inheritance (TEI). Experiments with Caenorhabditis elegans, which exhibits robust heritable epigenetic effects, demonstrated small RNAs as key factors of TEI. Here, we discuss three major barriers to TEI in animals, two of which, the “Weismann barrier” and germline epigenetic reprogramming, have been known for decades. These are thought to effectively prevent TEI in mammals but not to the same extent in C. elegans. We argue that a third barrier—that we termed “somatic epigenetic resetting”—may further inhibit TEI and, unlike the other two, restricts TEI in C. elegans as well. While epigenetic information can overcome the Weismann barrier and transmit from the soma to the germline, it usually cannot “travel back” directly from the germline to the soma in subsequent generations. Nevertheless, heritable germline memory may still influence the animal's physiology by indirectly modifying gene expression in somatic tissues.
Effect of lateral electronic diffusion on acoustic diffraction in picosecond ultrasonics

A diffracted picosecond ultrasonic field is generated by a 100 fs laser pulse focused onto a spot with diameter less than $1\text{ }\ensuremath{\mu}\text{m}$. As the pulse duration is shorter than the relaxation time of the electrons, the microscopic evolutions must be accounted for in metals. Following the absorption of the laser energy transported by the photons, electrons diffuse in all directions and simultaneously transfer their energy to the crystal lattice through collisions with phonons. The diffraction of the resulting electronic and phononic sources launches a three-dimensional (3D) ultrasonic field, containing bulk and surface waves. This microscopic generation process is here described with a 3D two-temperature model. A combination of Hankel and Fourier transforms allows the analytical solving of the temperature and elastic fields in the frequency--wave number domain. As expected, the highest frequencies composing the acoustic signal are affected by the quasi-instantaneous expansion of the electronic source, yet a theoretical analysis also demonstrates the influence of ultrafast electron dynamic on surface waves and on the low acoustic frequencies generated by diffraction. This conclusion is revealed by the study of the Rayleigh wave in a $2.1\text{\ensuremath{-}}\ensuremath{\mu}\text{m}$-thick gold film deposited on a semi-infinite silicon substrate. The good agreement between the calculated spatiotemporal signals and the experimental results supports the analytical predictions.
The overshoot region at the bottom of the solar convection zone

The extent and thermal stratification of the region of convective overshoot underneath the convection zone of the sun are investigated. The phenomenon of convective overshoot in general is discussed, and some of the modal and model approaches to studying it are briefly reviewed. A detailed theoretical description of the motion of plumes in a stably stratified medium is given, leading to a 'derivation' of the plume equations from the hydrodynamic equations. Entrainment is discussed, and it is shown how the plume equations can be used to compute convective overshoot in the sun. The limitations of the plume model are addressed, arguing that a thin boundary layer must exist which separates convective and radiative regions. The results of numerical integrations of the plume equations, as applied to the region of convective overshoot underneath the solar convective zone, are discussed.
Lie-EM-ICP algorithm: a novel frame for 2D shape registration

In this paper, a 2D shape registration algorithm for noisy data is established by combining the Iterative Closest Point (ICP) method, Expectation Maximization (EM) method, and Lie Group representation. First, the problem is formulated by a minimization problem with two sets of variables: the point-to-point correspondence, and the transformation (i.e., rotation, scaling and translation) between two data sets. The conventional way for solving this model is by iterating alternatively the following two steps: 1) having the transformation fixed, solve the correspondence, and 2) having the correspondence fixed, solve the transformation. In our approach, to enhance the robustness, the EM algorithm is introduced to find the correspondence by a probability which covers the relationship of all points, instead of one-to-one closest correspondence in ICP. Meanwhile, Lie group is used to parameterize transformation, i.e., in the iteration, the rotation, scaling and translation are all elements within respective Lie groups, and we use the element of Lie algebra to represent that of Lie group near the identity via exponential map. This forms a unified framework for registration algorithms. Then, transformation is estimated by solving a quadratic programming. The experimental result in 2D shape registration demonstrates that, compared with Lie-ICP, our algorithm is robuster and more accurate.
Social divisions and risk perception drive divergent epidemics and large later waves

Abstract Abstract During infectious disease outbreaks, individuals may adopt protective measures like vaccination and physical distancing in response to awareness of disease burden. Prior work showed how feedbacks between epidemic intensity and awareness-based behaviour shape disease dynamics. These models often overlook social divisions, where population subgroups may be disproportionately impacted by a disease and more responsive to the effects of disease within their group. We develop a compartmental model of disease transmission and awareness-based protective behaviour in a population split into two groups to explore the impacts of awareness separation (relatively greater in- vs. out-group awareness of epidemic severity) and mixing separation (relatively greater in- vs. out-group contact rates). Using simulations, we show that groups that are more separated in awareness have smaller differences in mortality. Fatigue (i.e. abandonment of protective measures over time) can drive additional infection waves that can even exceed the size of the initial wave, particularly if uniform awareness drives early protection in one group, leaving that group largely susceptible to future infection. Counterintuitively, vaccine or infection-acquired immunity that is more protective against transmission and mortality may indirectly lead to more infections by reducing perceived risk of infection and therefore vaccine uptake. Awareness-based protective behaviour, including awareness separation, can fundamentally alter disease dynamics. Social media summary: Depending on group division, behaviour based on perceived risk can change epidemic dynamics & produce large later waves.
Resisting Amnesia: Renewing and Expanding the Study of Suburban Inequality

Suburban inequality is the focus of this double issue of RSF: The Russell Sage Foundation Journal of the Social Sciences. This introduction addresses the limited related scholarship, describes how inequality unfolds differently in suburban communities than in urban and rural communities, and draws attention to urgent issues related to stratification between and within suburban communities. We argue that inattention to the study of suburban space, methodological and disciplinary silos, and the changing nature of the suburbs have left large holes in our understanding of how inequality operates. This critical review covers areas such as measurement, forgotten suburban scholarship, demographic change, suburban poverty, social supports, race, immigration, education, politics, policing, and future directions for suburban studies. In our call for resisting amnesia, we also draw attention to forgotten suburban histories and studies of a diverse range of suburban communities.
Research on improved DeepLabv3+ image Semantic Segmentation algorithm

Abstract: The location of the impurities in the oil and aqueous phases can be observed through an intelligent view mirror during solvent extraction. In order to accurately identify the separation region between the oil and impurity layers, this paper proposes an image semantic segmentation method with an optimised DeepLabv3+ model. The method is based on the DeepLabv3+ network and uses a lightweight EfficientNetv2 network to extract features from the shallow output of the network and improve parameter utilization. It also uses a strip pooling module instead of global average pooling in the Atrous Spatial Pyramid Pooling (ASPP) module, and introduces depth-separable inflationary convolution to reduce the number of parameters and improve the ability to learn multi-scale information; it uses a Pyramid Split Attention (PSA) to enhance the model representation power and enriches the geometric detail information of the image by extracting multiple shallow features of the backbone network. Experiments show that the algorithm achieves 80.13% mIoU with number of parameters, effectively optimising segmentation accuracy and model complexity, as well as improving model generalisation capability.
Computational Resource Allocation in Fog Computing: A Comprehensive Survey

Fog computing is a paradigm that allows the provisioning of computational resources and services at the edge of the network, closer to the end devices and users, complementing cloud computing. The heterogeneity and large number of devices are challenges to obtaining optimized resource allocation in this environment. Over time, some surveys have been presented on resource management in fog computing. However, they now lack a broader and deeper view about this subject, considering the recent publications. This article presents a systematic literature review with a focus on resource allocation for fog computing, and in a more comprehensive way than the existing works. The survey is based on 108 selected publications from 2012 to 2022. The analysis has exposed their main techniques, metrics used, evaluation tools, virtualization methods, architecture, and domains where the proposed solutions were applied. The results show an updated and comprehensive view about resource allocation in fog computing. The main challenges and open research questions are discussed, and a new fog computing resource management cycle is proposed.