Miracle-dz/UniFAR-FTUs huggingface dataset:
Scaling of post-contractile phosphocreatine recovery in white muscle of black sea bass, Centropristis striata

During somatic growth, increases in fish muscle mass occur both by hyperplasia and hypertrophy, and in some species the hypertrophic phase of growth leads to very large fiber diameters. Large fiber size leads is associated with low fiber surface area to volume (SA:V), which may (1) limit O2 flux across the sarcolemmal, (2) create potentially large intracellular diffusion distances between mitochondria, and (3) lead to diffusive constraints on aerobic metabolism. This study examined the effects of intracellular metabolite diffusion by investigating how the rate of post-contractile phosphocreatine (PCr) recovery in isolated epaxial white muscle from black sea bass (Centropristis striata) scales with body mass (and fiber size). Isolated muscle fibers from different sized fish (5.7 to 4159.4 g) were stimulated until PCr was depleted. The use of isolated fiber bundles in a high PO2 superfusion medium eliminated the confounding effects of fiber SA:V on oxygen flux across the membranes. Light microscopy and transmission electron microscopy techniques were employed to characterize fiber size and intracellular structure. White muscle fiber diameters increased significantly during growth, and became very large in adult fish (>250 µm). Mitochondrial density and cytochrome-c oxidase (COX) activity scaled negatively with increasing body mass, and had similar scaling exponents to each other. Sub-sarcolemmal mitochondrial volume per sarcolemmal membrane area significantly increased during fiber growth, indicating a shift in mitochondria towards areas of higher PO2 at the periphery of the fiber. Despite differences in fiber size, aerobic capacity, and intracellular diffusion distances between size classes, the post-contractile recovery rate of PCr was size independent. Further, a mathematical reaction-diffusion analysis indicated that the rate of PCr resynthesis was too slow to be limited by intracellular metabolite diffusion. These results suggest that in these white fibers, the rate of PCr recovery is limited by the low mitochondrial density. Additionally, the change in mitochondrial distribution with increasing fiber size suggests that low SA:V and limited O2 flux is a more important design constraint in large fibers of fish white muscle than is intracellular metabolite flux.
Spatial evaluation of switchgrass productivity under historical and future climate scenarios in Michigan

Switchgrass (Panicum virgatum) productivity on marginal and fertile lands has not been thoroughly evaluated in a systematic manner that includes soil–crop–weather–management interactions and to quantify the risk of failure or success in growing the crop. We used the Systems Approach to Land Use Sustainability (SALUS) model to identify areas with low risk of failing to having more than 8000 kg ha−1 yr−1 switchgrass aboveground net primary productivity (ANPP) under rainfed and unfertilized conditions. In addition, we diagnosed constraining factors for switchgrass growth, and tested the effect of nitrogen fertilizer application on plant productivity across Michigan for 30 years under three climate scenarios (baseline climate in 1981–2010, future climate with emissions using RCP 2.6 and RCP 6.0). We determined that <16% of land in Michigan may have at least 8 Mg ha−1 yr−1 ANPP under rainfed and unfertilized management with a low risk of failure. Of the productive low‐risk land, about 25% was marginal land, with more than 80% of which was affected by limited water availability due to low soil water‐holding capacity and shallow depth. About 80% of the marginal land was N limited under baseline conditions, but that percentage decreased to 58.5% and 42.1% under RCP 2.6 and RCP 6.0 climate scenarios, respectively, partly due to shorter growing season, smaller plants and less N demand. We also found that the majority of Michigan's land could have high switchgrass ANPP and low risk of failure with no more than 60 kgN ha−1 fertilizer input. We believe that the methodology used in this study works at different spatial scales, as well as for other biofuel crops.
Comparing Keyword-based Query Processing over RDF Datasets and Relational Databases

This paper compares keyword-based query processing in two environments: RDF datasets with schemas and relational databases. The comparison is based on a tool that first translates a keyword-based query into an abstract query, and then compiles the abstract query into a SPARQL or a SQL query such that each result of the SPARQL or SQL query is an answer for the keyword-based query. The tool explores the schema to avoid user intervention during the translation process. The paper includes extensive experiments to compare keywordbased query processing in the two environments, using a full version of IMDb – The Internet Movies Database, and the Mondial database.
Natural Wax for Transient Electronics

Emerging classes of bioresorbable electronic materials serve as the basis for active biomedical implants that are capable of providing sensing, monitoring, stimulating, and other forms of function over an operating period matched to biological processes such as wound healing. These platforms are of interest because subsequent dissolution, enzymatic degradation, and/or bioresorption can eliminate the need for surgical extraction. This report introduces natural wax materials as long‐lived, hydrophobic encapsulation layers for such systems, where biodegradation eventually occurs by chain scission. Studies of wax stability as an encapsulation material demonstrate the ability to retain operation of underlying biodegradable electronic systems for durations between a few days to a few weeks during complete immersion in aqueous solutions in ex‐vivo physiological conditions. Electrically conductive composites result from the addition of tungsten micro/nanoparticles, as a conductive, printable paste with similar lifetimes. Demonstrations of these materials in partially biodegradable wireless light‐emitting diodes and near‐field communication circuits illustrate their use in functional bioresorbable electronic systems. Investigations in animal models reveal no signs of toxicity or other adverse biological responses.
A Multi-Decadal Change Analysis for Irrigation Ponds in Taoyuan, Taiwan Using Multi-source Data

A multi-decadal change analysis of the irrigation ponds in Taoyuan, Taiwan was conducted by using multi-source data including digitized ancient maps, declassified single-band CORONA satellite images, and multispectral SPOT images. Supervised LULC classifications were conducted using four textural features derived from the single-band CORONA images and spectral features derived from SPOT images. Post-classification analysis revealed that the number of irrigation ponds in the study area decreased during the post-World War II farmland consolidation period (1945 – 1965) and the subsequent industrialization period (1970 – 2000). However, efforts on restoration of irrigation ponds in recent years have resulted in gradual increases in the number (9%) and total area (12%) of irrigation ponds in the study area.
Sensitivity improvements for Shack–Hartmann wavefront sensors using total variation minimization

We investigate the improvements in Shack–Hartmann wavefront sensor image processing that can be realized using total variation minimization techniques to remove noise from these images. We perform Monte Carlo simulation to demonstrate that at certain signal-to-noise levels, sensitivity improvements of up to one astronomical magnitude can be realized. We also present on-sky measurements taken with the CANARY adaptive optics system that demonstrate an improvement in performance when this technique is employed, and show that this algorithm can be implemented in a real-time control system. We conclude that total variation minimization can lead to improvements in sensitivity of up to one astronomical magnitude when used with adaptive optics systems.
Making a vampire

The modern vampire is often portrayed as a human transformed into a vampire due to a bloodthirsty spirit1, demons2, viruses and other pathogens3, magic or some unknown reason4. Neither fiction nor more realistic accounts have shed light on the precise molecular mechanisms of how the transformation happens until the novel trilogy and TV series called The Strain (Fig. 1) introduced some ways as to how the transformation could happen. In The Strain, parasitic worms carry a virus that causes the vampiric changes to happen through a modification in the expression of genes. This change even creates new organs such as the stinger. For obvious reasons, no actual experimental studies have been conducted with vampires and so the exact origin and evolution of vampirism remains unknown. A full genomewide association study or transcriptome
Sensing Earthquake Disaster Information: A Named Entity Recognition Approach Using Twitter Collaborative Data

In recent years, online social networks have received important consideration in spatial modelling fields given the critical information that can be extracted from them for events in real time; one of the most latent issues is that regarding various natural disasters such as earthquakes. Although it is possible to retrieve data from these social networks with embedded geographic information provided by GPS, in many cases this is not possible. An alternative solution is to reconstruct specific locations using probabilistic language models, more specifically those based on Name Entity Recognition (NER), which extracts names from a user’s description about an event occurring in a specific place (e.g., a collapsed building on a specific avenue). In this work, we present a methodology to use twitter as a social sensor system for disasters. The methodology scores NER locations with a kernel density estimation function for different subtopics originating from a natural disaster and that maps them into a geographic space is proposed. The proposed methodology is evaluated with tweets related to the 2017 earthquake in Mexico.
Dual Band Filter Design Using Perturbed Square Patch Resonator

In this paper a dual band pass filter has been designed using perturbed square patch resonator. In the basic design a square patch resonator is considered which resonates at the higher value of two center frequencies. The patch is then modified to produce another pass band at lower end. A small rectangular slot has been made on the ground plane due to which insertion loss characteristic have been enhanced. The proposed design is simple and easy to implement. There is a very good agreement between the simulated and measured results.
A Tractable Approach to Pass-Through Patterns

For tractability, researchers often use equilibrium models that can be solved in closed-form. In practice, this means imposing unintended substantive restrictions on incidence properties that are central to many policy questions. To overcome this limitation, we characterize a set of joint supply and demand systems yielding closed-form solutions. This class is broad enough to allow substantial flexibility and thus realism, and it nests virtually all other tractable systems in the literature. We apply these more realistic structures to a range of international trade models typically solved in closed-form, thereby deriving several applied insights about, e.g., the cyclicality of wage bargaining and the organization of supply chains. Beyond parametric examples, the Laplace Transform, a standard tool used in applied mathematics and physics in analogous settings that we exploit, provides a general approach to characterizing and approximating incidence at any degree of desired tractability.
Effect of selected herbicides on growth and lipid content of Nannochloris oculata

Nannochloris oculata (Droop) D.J. Hibberd has attracted attention as a potential source of biofuels because of high oil content and rapid growth rate. The effect of selected herbicides on algal growth and total lipid content was examined. Twenty-two herbicides representing 14 modes of action were assayed. Photosystem II inhibitor diuron was the most toxic herbicide to algal growth. At low concentrations, sethoxydim was not toxic to algae but decreased its lipid content significantly. Photosystem I inhibitor diquat at low concentration did not affect algal growth, but algal growth inhibition increased with increasing concentration. Diquat at 0.1 and 1 mg L 1 decreased lipid content to 8.66 and 8.53%, respectively. At 5 mg L , glyphosate stimulated algal growth but decreased lipid content to 5.60% of dry weight. S-metolachlor had a significant effect on both algal biomass and lipid content. Smetolachlor at 0.1 mg L 1 decreased algal biomass to 75% of untreated control and decreased lipid content from 13.33 to 6.21% of dry weight. Fluridone at 0.1 mg L 1 decreased algal biomass to 84% of untreated and completely killed algae when the concentration increased to 1 mg L . Simazine at 0.1 mg L 1 had no significant effect on algal growth but decreased lipid content from 13.33 to 5.15% of dry weight. Pendimethalin and dinoterb had no significant effect on algal growth but reduced lipid content to 6.19 and 6.03%, respectively. The use of algae as a source of fuel will undoubtedly require the use of outdoor, openpond systems. These results will be useful for developing management systems to control invasive algal species in outdoor, open-pond systems, ultimately keeping the oilproducing algae pure.
SimCells , an advanced software for multicellular modeling Application to tumoral and blood vessel co-development

New biomedical advances at cellular level give the possibility to develop more and more accurate computational models of cells. Moreover, the increasing power of graphical processor units allows the simulation of millions of interacting virtual cells. This paper summarizes efforts made to create multicellular simulators, their attended benefits and their inevitable drawbacks. In particular, it presents the new software SimCells that simulate the dynamics of multicellular systems using a graphically programmable multiagent system. A fully functional example of the tumoral and blood vessel codevelopment is also detailed.
Multiscale modeling of cellular epigenetic states and tissue patterning : stochasticity in molecular network , chromatin folding in cell nucleus , and cell-cell interactions in tissue patterning

Genome sequences provide the overall genetic blueprint of cells, cells possessing the same genome can exhibit diverse phenotypes. There is a multitude of mechanisms controlling cellular epigenetic states and that dictate the behavior of cells. Among these, networks of interacting molecules, often under stochastic control, depending on the specific wirings of molecular components and the physiological conditions, can have a different landscape of cellular states. In addition, chromosome folding in three-dimensional space provides another important control mechanism for selective activation and repression of gene expression. Fully differentiated cells with different properties grow, divide, and interact through mechanical forces and communicate through signal transduction, resulting in the formation of complex tissue patterns. Developing quantitative models to study these multi-scale phenomena and to identify opportunities for improving human health requires development of theoretical models, algorithms, and computational tools. Here we review recent progress made in these important directions.
Soil mycorrhizal and nematode diversity vary in response to bioenergy crop identity and fertilization

The mandate by the Energy Independence and Security Act of 2007 to increase renewable fuel production in the USA has resulted in extensive research into the sustainability of perennial bioenergy crops such as switchgrass (Panicum virgatum) and miscanthus (Miscanthus× giganteus). Perennial grassland crops have been shown to support greater aboveground biodiversity and ecosystem function than annual crops. However, management considerations, such as what crop to plant or whether to use fertilizer, may alter belowground diversity and ecosystem functioning associated with these grasslands as well. In this study, we compared crop type (switchgrass or miscanthus) and nitrogen fertilization effects on arbuscular mycorrhizal fungal (AMF) and soil nematode abundance, activity, and diversity in a long‐term experiment. We quantified AMF root colonization, AMF extra‐radical hyphal length, soil glomalin concentrations, AMF richness and diversity, plant‐parasitic nematode abundance, and nematode family richness and diversity in each treatment. Mycorrhizal activity and diversity were higher with switchgrass than with miscanthus, leading to higher potential soil carbon contributions via increased hyphal growth and glomalin production. Plant‐parasitic nematode (PPN) abundance was 2.3 × higher in miscanthus plots compared to switchgrass, mostly due to increases in dagger nematodes (Xiphinema). The higher PPN abundance in miscanthus may be a consequence of lower AMF in this species, as AMF can provide protection against PPN through a variety of mechanisms. Nitrogen fertilization had minor negative effects on AMF and nematode diversity associated with these crops. Overall, we found that crop type and fertilizer application associated with perennial bioenergy cropping systems can have detectable effects on the diversity and composition of soil communities, which may have important consequences for the ecosystem services provided by these systems.
Energy-Efficient Multiple Producer-Consumer

Hardware energy efficiency has been one of the prominent objectives of system design in the last two decades. However, with the recent explosion in mobile computing and the increasing demand for green data centers, software energy efficiency has also risen to be an equally important factor. The majority of classic concurrency control algorithms were designed in an era when energy efficiency was not an important dimension in algorithm design. Concurrency control algorithms are applied to solve a wide range of problems from kernel-level primitives in operating systems to networking devices and web services. These primitives and services are constantly and heavily invoked in any computing system and by a larger scale in networking devices and data centers. Thus, even a small change in their energy spectrum can make a huge impact on overall energy consumption for long periods of time. This paper focuses on the classic producer-consumer problem. First, we study the energy profile of a set of existing producer-consumer algorithms. In particular, we present evidence that although these algorithms share the same functional goals, their behavior with respect to energy consumption are drastically different. Then, we present a dynamic algorithm for the multiple producer-consumer problem, where consumers in a multicore system use learning mechanisms to predict the rate of production, and effectively utilize this prediction to attempt to latch onto previously scheduled CPU wake-ups. Such group latching increases the idle time between consumer activations resulting in more CPU idle time and, hence, lower average CPU frequency. This in turn reduces energy consumption. We enable consumers to dynamically reserve more pre-allocated memory in cases where the production rate is too high. Consumers may compete for the extra space and dynamically release it when it is no longer needed. Our experiments show that our algorithm provides a 38 percent decrease in energy consumption compared to a mainstream semaphore-based producer-consumer implementation when running 10 parallel consumers. We validate the effectiveness of our algorithm with a set of thorough experiments on varying parameters of scalability. Finally, we present our recommendations on when our algorithm is most beneficial.
0 SPACE-TA : CostE ective Task Allocation Exploiting Intra-and Inter-Data Correlations in Sparse Crowdsensing

Data quality and budget are two primary concerns in urban-scale mobile crowdsensing. Traditional research on mobile crowdsensing mainly takes sensing coverage ratio as the data quality metric, rather than the overall sensed data error in the target sensing area. In this paper, we propose to leverage spatio-temporal correlations among the sensed data in the target sensing area to signicantly reduce the number of sensing task assignments. In particular, we exploit both intra-data correlations within the same type of sensed data and inter-data correlations among dierent types of sensed data in the sensing task. We propose a novel crowdsensing task allocation framework called SPACE-TA (SPArse Cost-Eective Task Allocation), combining compressive sensing, statistical analysis, active learning and transfer learning, to dynamically select a small set of sub-areas for sensing in each timeslot (cycle), while inferring the data of unsensed sub-areas under a probabilistic data quality guarantee. Evaluations on real-life temperature, humidity, air quality, and trac monitoring datasets verify the eectiveness of SPACE-TA. In the temperature monitoring task leveraging intra-data correlations, SPACE-TA requires data from only 15.5% of the sub-areas while keeping the inference error below 0.25◦C in 95% of the cycles, reducing the number of sensed sub-areas by 18.0-26.5% compared to baselines. When multiple tasks run simultaneously, e.g., for temperature and humidity monitoring, SPACE-TA can further reduce ∼10% of the sensed sub-areas by exploiting inter-data correlations.