Miracle-dz/UniFAR-FTUs huggingface dataset:
Biological Ion Transporters as Gating Devices for Chemomechanical and Chemoelectrical Energy Conversion

This dissertation presents a new class of engineered devices, fabricated from synthetic materials and protein transporters extracted from cell membranes of plants, that use chemomechanical and chemoelectrical energy conversion processes to perform mechanical and electrical work. The chemomechanical energy conversion concept is implemented in a protein based actuator. The chemical energy is applied as an electrochemical gradient of protons across a membrane assembly formed from phospholipids and SUT4 -a proton-sucrose cotransporter. The membrane assembly forms a physical barrier between two chambers in the actuator. The SUT4 proteins in the membrane assembly balances the applied electrochemical gradient by a concentration gradient of sucrose across the membrane. The sucrose gradient simultaneously generates an osmotic flow which deforms a flexible wall in a constrained chamber of the actuator, thus exhibiting mechanical strain. The sucrose concentration balanced by the protein transporter is used as the control variable for fluid flow through the membrane. The transport properties of the membrane assembly has been characterized for the control variable in the system. The reaction kinetics based model for solute transport through the cotransporter is modified to compute the equilibrium constant for solute binding and fluid translocation rate through the membrane. The maximum initial flux rate through the membrane is computed to be 2.51±0.6 μl/μg. cm2.min for an applied pH4.0/pH7.0 concentration gradient across the membrane. The flux rate can be modulated by varying the sucrose concentration in the actuator. The prototype actuator has been
Economics of Sustainable Intensification of Aquaculture: Evidence from Shrimp Farms in Vietnam and Thailand

There is growing interest in sustainable intensification of aquaculture production. Yet little economic analysis has been done on farm-level effects of the economic sustainability of production intensification. Data from 83 shrimp farms (43 in Vietnam and 40 in Thailand) were used to identify (through principal component and cluster analyses) 13 clusters of management practices that reflected various scales of production intensity that ranged from 0–1999 kg/ha/crop to 10,000 kg/ha/crop and above, for both Penaeus monodon and Litopenaeus vannamei in Vietnam and Thailand. The clusters identified reflected sets of management practices that resulted in differing yields despite similarities in stocking densities among some clusters. The enterprise budget analysis developed showed that the more intensively managed clusters outperformed the less intensively managed clusters in economic terms. More intensively managed farm clusters had lower costs per metric ton of shrimp produced and were more profitable. The greater yields of shrimp produced per hectare of land and water resources in more intensively managed shrimp farms spread annual fixed costs across a greater volume of shrimp produced and reduced the cost per metric ton of shrimp. Costs per metric ton of shrimp produced decreased from the lowest to the highest intensity level (from US$10,245 at lowest intensity to US$3484 at highest for P. monodon and from US$24,301 to US$5387 for L. vannamei in Vietnam and from US$8184 at the lowest intensity level to US$3817 at the highest intensity level per metric ton for L. vannamei in Thailand). Costs of pond amendments used in shrimp production were particularly high in Vietnam and largely unwarranted, whereas fixed costs associated with the value of land, production facilities, equipment, and labor were sufficiently high in Thailand so that net returns were negative in the long run. Nevertheless, economic losses in Thailand were less at greater levels of intensification. The study demonstrated a clear value proposition for shrimp farmers to use natural resources (such as land) and other inputs in an efficient manner and supports findings from corresponding research on farm-level natural resource use efficiency. Additional research that incorporates economic analysis into on-farm studies of sustainable intensification of aquaculture is needed to provide ongoing guidance related to sustainable management practices for aquaculture.
A Novel Unsupervised Change Detection Approach Based On Spectral Transformation For Multispectral Images

Change detection (CD) for multispectral remote sensing images is an important approach to observe the changes of the earth. However, the same object usually has different spectra in multi-temporal images, which is one of the biggest challenges for CD. To overcome this problem, a novel unsupervised CD approach based on spectral transformation and joint spectral-spatial feature learning (STCD) is proposed for multispectral images in this paper. By exploring the relationship between imaging environment and the object spectra, the spectral transformation is used to suppress the phenomenon of “same object with different spectra”. Besides, a detection network with joint spectral-spatial feature learning is designed to extract the spectral-spatial features simultaneously to make the CD algorithm more robust. Both theoretical analyses and experiment results proved that the proposed STCD method is superior to the state-of-the-art unsupervised methods on multispectral images CD.
Photodynamic Priming Modulates Endothelial Cell–Cell Junction Phenotype for Light-Activated Remote Control of Drug Delivery

The blood–brain barrier (BBB) remains a major obstacle for drug delivery to the central nervous system. In particular, the tight and adherens junctions that join the brain capillary endothelial cells limit the diffusion of various molecules from the bloodstream into the brain. Photodynamic priming (PDP) is a non-cytotoxic modality that involves light activation of photosensitizers to photochemically modulate nearby molecules without killing the cells. Here we investigate the effects of sub-lethal photochemistry on junction phenotype (i.e., continuous, punctate, or perpendicular), as well as the BBB permeability in a transwell model of human brain microvascular endothelial cells (HBMECs). We showed that PDP decreases the continuous junction architecture by ∼20%, increases the perpendicular junction architecture by ∼40%, and has minimal impact on cell morphology in HBMECs. Furthermore, transwell permeability assay revealed that PDP improves the HBMEC permeability to dextran or nanoliposomes by up to 30-fold for 6-9 days. These results suggest that PDP could safely reverse the mature brain endothelial junctions without killing the HBMECs. This study not only emphasizes the critical roles of PDP in the modulation junction phenotype, but also highlights the opportunity to further develop PDP-based combinations that opens the cerebrum endothelium for enhanced drug transporter across the BBB.
Microsaccadic Eye Movements but not Pupillary Dilation Response Characterizes the Crossmodal Freezing Effect

Abstract In typical spatial orienting tasks, the perception of crossmodal (e.g., audiovisual) stimuli evokes greater pupil dilation and microsaccade inhibition than unisensory stimuli (e.g., visual). The characteristic pupil dilation and microsaccade inhibition has been observed in response to “salient” events/stimuli. Although the “saliency” account is appealing in the spatial domain, whether this occurs in the temporal context remains largely unknown. Here, in a brief temporal scale (within 1 s) and with the working mechanism of involuntary temporal attention, we investigated how eye metric characteristics reflect the temporal dynamics of perceptual organization, with and without multisensory integration. We adopted the crossmodal freezing paradigm using the classical Ternus apparent motion. Results showed that synchronous beeps biased the perceptual report for group motion and triggered the prolonged sound-induced oculomotor inhibition (OMI), whereas the sound-induced OMI was not obvious in a crossmodal task-free scenario (visual localization without audiovisual integration). A general pupil dilation response was observed in the presence of sounds in both visual Ternus motion categorization and visual localization tasks. This study provides the first empirical account of crossmodal integration by capturing microsaccades within a brief temporal scale; OMI but not pupillary dilation response characterizes task-specific audiovisual integration (shown by the crossmodal freezing effect).
Estimating the value of quarantine: eradicating invasive cane toads from tropical islands

Islands are increasingly used to protect endangered populations from the negative impacts of invasive species. Quarantine efforts on islands are typically undervalued, however. Using a field-based removal experiment, we estimate the economic value of quarantine efforts aimed at keeping invasive cane toads (Rhinella marina) off Australian islands. We estimate a mean density of 3444 [2744, 4386] individual toads per km2 and a mean per-night detection probability of 0.1 [0.07,0.13]. Using a removal model and estimates of economic costs incurred during toad removal, we estimate that eradicating cane toads would cost AUD$96,556 per km2. Across islands that have been prioritized for conservation benefit across the toads predicted range, we estimate the remaining value of toad quarantine to be more than $1.3 billion. The value of a proposed waterless barrier on the mainland to prevent the spread of toads into the Pilbara was in excess of $26 billion. We conclude that quarantine of toads across Australia provides substantial value in prevented eradication costs.
Mutational Analysis of the Binding of Alternative Substrates and Inhibitors to the Active Site of Human Glutathione Transferase P1–1

Glutathione transferases (GSTs) are enzymes that play a critical role in cellular detoxication by catalyzing the nucleophilic attack of glutathione on the electrophilic center of a number of xenobiotic compounds, including many therapeutic drugs. Mutations of amino acid residues in the glutathione-binding site of human glutathione transferase P1–1, namely W39C, K45A, Q52A, Q52K, and Q52E, have been engineered. The recombinant mutant proteins were expressed in Escherichia coli, but only mutants K45A, Q52A, and Q52K showed measurable activity. Steady-state kinetics comparing glutathione with the alternative thiol substrate γ-glutamylcysteine demonstrated the importance of the glycine residue in glutathione for high catalytic efficiency. Inhibition experiments with a set of glutathione analogs structurally related to the therapeutic drugs Telintra and Telcyta enabled determination of binding energies that were contributed by different substituents. The effects of substituting amino acid side chains in the glutathione-binding site of the enzyme on binding the glutathione derivatives and catalysis were evaluated.
Component analysis of 3D elastic 9C full-waveform inversion: Ettlingen Line case study

Full Waveform Inversion (FWI) is one of the most popular seismic imaging techniques. In the exploration scale, FWI has become one of the industrial standards and proven to be accurate. Following that trend, FWI in shallow seismic scale also starts to gain attraction in the past decade. Several publications have demonstrated and proposed workflow to tackle the challenges in shallow seismic scales, such as sparse and limited acquisition, weak signal to noise ratio, high complexity propagation due to the strong elastic effect, and strong attenuation. In this research, we focus on the analysis of the effect of multicomponent data in shallow seismic scale towards 3D elastic FWI. The experiment’s target is the Ettlingen Line (EL), a defensive trench-line which was built by the German Troop in 1707, located at Rheinstetten, Germany. We perform both synthetic (using cartesian direction’s source) and field data (using Galperin source) in order to demonstrate the effect of multi-component data on FWI. Sixteen component combinations are analyzed for each case. By doing so, we find out that incorporating multi-component data generally has a positive impact on FWI in terms of model and data misfit, especially if the horizontal components are taken into account. The importance of each component can be used for future shallow seismic acquisition design for FWI with similar conditions.
Profiling the Sustainability of Stock Exchanges at Global Level through an Optimal Scaling Process by Applying CATPCA

The issue of investigating the sustainability of stock exchanges is particularly relevant in the context of sustainable finance. The research objective of the present paper is to analyse the sustainability of stock exchanges based on the construction of an original multi-variate composite index in order to explore the links with business-specific and national environment indicators. We conducted our global study on 92 eligible out of a total of 96 available stock exchanges on the Sustainable Stock Exchanges Initiative (SSE) platform at the end of August 2019. The overall sustainability index of stock exchanges (SustyEx) was developed by successively applying the Categorical Principal Component Analysis (CATPCA) at pillar and aggregated levels. The three-grouping solution highlighted the inclusion of most of the investigated stock exchanges in the initial sustainability development stage. The sustainability achievements of stock exchanges are frequently associated with their internal and external economic performance.
A Study On Light Field Denoising For 3d Consistent Visualization

We propose a novel method of light field denoising for 3D consistent visualization. Light field data are often significantly degraded by awful noise due to lack of exposure under insufficient lighting, especially, if acquired by a lens array. Then, recent studies notice that a 4D light field corresponds to structured multi-view images that are correlated to each other well according to 3D scenes. For example, a CNN-based denoising method utilizes the correlation by analyzing various subspaces of 4D light fields. In this paper, 4D light field denoising is achieved by applying simple restoration based on Total Variation minimization to small images composed of corresponding pixels extracted from multi-view images. We show experimental results using synthetic and real images to clarify how our proposed method effectively works for 3D consistent visualization in comparison with the other methods. In addition, we discuss possible future improvement of the proposed method when integrating our novel approach with the conventional 2D image denoising for more effective light field denoising.
Do seed transfer zones for ecological restoration reflect the spatial genetic variation of the common grassland species Lathyrus pratensis?

A common ecological restoration approach is the reestablishment of vegetation using seed mixtures. To preserve the natural genetic pattern of plant species local seed material should be used. Consequently, seed transfer zones (seed production areas and seed provenance regions) have been delineated for ecological restoration in Germany. Although it is assumed that these transfer zones represent genetic variation, there remains a lack of empirical data. In this study, we analyzed whether seed transfer zones reflect the genetic variation of the common grassland species Lathyrus pratensis. We sampled 706 individuals from 37 populations in Bavaria, Germany and analyzed genetic variation using amplified fragment length polymorphisms. In our study, we observed higher levels of genetic variation and fragment rarity in the southern Bavarian populations compared to northern populations. Our analyses revealed a strong genetic differentiation between southern and northern Bavarian populations delineated along the Danube River. However, seed production areas and seed provenance regions reflected genetic variation of L. pratensis only to a limited degree. Our study illustrates that the level of genetic variation within populations strongly depends on population history. Furthermore, the geomorphological and climatic attributes, which have been used to delineate seed provenance regions, do not reduce gene flow among populations. Seed collections for gene banks and seed production should comprise seeds from populations in southern and northern Bavaria representing the strong genetic variation between both regions, but prioritize southern populations due to higher levels of variation.
On edge-path eigenvalues of graphs

ABSTRACT Let G be a graph with vertex set and be an matrix whose -entry is the maximum number of internally edge-disjoint paths between and , if , and zero otherwise. Also, define , where D is a diagonal matrix whose i-th diagonal element is the number of edge-disjoint cycles containing , whose is a multiple of J−I. Among other results, we determine the spectrum and the energy of the matrix for an arbitrary bicyclic graph G.
List of Figures/Tables

The aim of this paper is to estimate income advanta ges arising from publicly provided education and to analyse their impact on the income dist ribution in Germany. Using representative micro-data from the SOEP and considering regional a d education specific variation, the overall result is an expected levelling effect in a cross-sectional perspective. However, approximating the accumulating effects over the life course within a regression framework – controlling for selectivity arising from the existe nce of children as potential beneficiaries of educational transfers – we find evidence for social inequalities to be reinforced especially by public transfers for non-compulsory education in an intergenerational perspective.
Live Demonstration: Multi-Laptop HEVC Encoding

This paper presents a demonstration setup for distributed real-time HEVC encoding on a multi-computer system. The demonstrated multi-level parallelization scheme is implemented in the practical Kvazaar open-source HEVC encoder. It allows Kvazaar to exploit parallelism at three levels: 1) Single Instruction Multiple Data (SIMD) optimized coding tools at the data level; 2) Wavefront Parallel Processing (WPP) and Overlapped Wavefront (OWF) parallelization strategies at the thread level; and 3) distributed slice encoding on multi-computer systems at the process level. This interactive demonstration allows visitors to gradually increase the degree of parallelism in Kvazaar and see the benefits of parallelization in live HEVC encoding. Exploiting all three levels of parallelism on a three-laptop setup speeds up Kvazaar by almost 21× over a non-parallelized single-core implementation of Kvazaar.
Analysis of influencing factors of grain yield based on multiple linear regression

Food security is a strategic issue affecting economic development and social stability and agriculture has always been at the forefront of national economic development. As a large agricultural country and a country with a large population, the production of grain is of great importance to China. Therefore, in order to ensure national food security and assist the food administrative department in making scientific and effective decisions, it is significant to study the law of variance in grain production and make accurate forecasting of its development trend. This paper constructs the stepwise regression model and principal component regression to analyze the influencing factors of grain yield respectively and compares these two models in terms of their accuracy in prediction. After conducting the two regressions, this paper concludes that the two models both explain the variance in grain yield ideally, but from the aspect of accuracy in prediction, the principal component regression is more effective than stepwise linear regression.
Evaluating company bankruptcies using causal forests

ABSTRACT This study sought to analyze the variables that can influence company bankruptcy. For several years, the main studies on bankruptcy reported on the conventional methodologies with the aim of predicting it. In their analyses, the use of accounting variables was massively predominant. However, when applying them, the accounting variables were considered as homogenous; that is, for the traditional models, it was assumed that in all companies the behavior of the indicators was similar, and the heterogeneity among them was ignored. The relevance of the financial crisis that occurred at the end of 2007 is also observed; it caused a major global financial collapse, which had different effects on a wide variety of sectors and companies. Within this context, research that aims to identify problems such as the heterogeneity among companies and analyze the diversities among them are gaining relevance, given that the sector-related characteristics of capital structure and size, among others, vary depending on the company. Based on this, new approaches applied to bankruptcy prediction modeling should consider the heterogeneity among companies, aiming to improve the models used even more. A causal tree and forest were used together with quarterly accounting and sector-related data on 1,247 companies, 66 of which were bankrupt, 44 going bankrupt after 2008 and 22 before. The results showed that there is unobserved heterogeneity when the company bankruptcy processes are analyzed, raising questions about the traditional models such as discriminant analysis and logit, among others. Consequently, with the large volume in terms of dimensions, it was observed that there may be a functional form capable of explaining company bankruptcy, but this is not linear. It is also highlighted that there are sectors that are more prone to financial crises, aggravating the bankruptcy process.
Dynamic output feedback control for continuous-time Markov jump linear systems with hidden Markov models

In this work, we study the design of dynamic output feedback controllers for continuous-time Markov jump linear systems in the worst-case scenario of partial observation of both, the Markov chain and the state, through an iterative method. We assume that the controller has only access to the output of a fault-detection and isolation device and present design conditions for the , , and mixed controller that switches according only to the detector. As a by-product of our formulation, we are also able to design mode-dependent and independent controllers, and briefly discuss the design of filters depending on the detector. The results are given in terms of bilinear matrix inequalities that allow for an iterative separation procedure method in which in each step, we solve a linear matrix inequality problem. We also present an illustrative example in the context of systems subject to faults.
CGO: Multiband Astronomical Source Detection With Component-Graphs

Component-graphs provide powerful and complex structures for multi-band image processing. We propose a multiband astronomical source detection framework with the component-graphs relying on a new set of component attributes. We propose two modules to differentiate nodes belong to distinct objects and to detect partial object nodes. Experiments demonstrate an improved capacity at detecting faint objects on a multi-band astronomical dataset.