Miracle-dz/UniFAR-FTUs huggingface dataset:
A Model of the Coupling between Respiration, Active Processes and Passive Transport

Abstract A biochemically-aggregated model is introduced which captures the essential features of the coupling between respiration and active (energy-requiring) plant processes. Each active process is characterized as the conversion of ATP and NADPH (represented by X*) and a substrate (S) to ADP and NADP (represented by X) and a product (P) (e.g. for protein synthesis, S = amino-acids, P = protein). For each process, respiration generates X* and CO 2 from glucose (C) and X. Respiration and active processes are thus coupled through the turnover of ATP and NADPH, with C and S representing, respectively, the main energetic and material substrates of the overall reaction C + S → CO 2 + P. The model assumes mass action kinetics for the reaction rates, and incorporates passive transport of C and S to the reaction sites from an external region (e.g. phloem) with substrate concentrations C e and S e . The behaviour of this coupled respiration—active process—passive transport model is explored analytically. The main results are as follows: (1) In general, the respiration rate coupled to a given active process S → P has a non-rectangular hyperbolic dependence on C e and S e . (2) Because glucose provides both the energetic and material substrates for structural growth (cellulose synthesis), the associated respiration rate is proportional to C e . (3) When the passive transport of C and/or S for the process S → P becomes limiting, the associated respiration rate reduces to a ‘Blackmann response’ which is either entirely C-limited or entirely S-limited, depending on the relative availability of C e and S e . (4) These predictions are used to interpret empirically-derived growth and maintenance respiration coefficients, as well as widely-reported observations concerning the respiration/photosynthesis ratio and the response of respiration to carbohydrate concentration. (5) It is concluded that the model provides a simple, realistic, physiologically-based representation of the components of respiration, which can be used in plant growth models that separate substrates from structure.
Walnut Inspired Silicon Carbon Composites for Stable Lithium Ions Battery Anodes

The distinct quality of silicon (Si) makes it a natural choice for employment as a competitive anode material in rechargeable high specific energy lithium-ion batteries (LIBs) for practical applications. However, the Si-based LIBs are still hindered for practical applications due to the weak electrical conductivity and unstable solid electrolyte interfaces (SEI). New structures with enhanced conduction are highly desired to push the advance of Si-based LIBs. Herein, the Si nanoparticles coated by few-layer graphene (fGra) has been wrapped into honeycomb porous carbon (Pc) framework with good Si-C contact and reliable void via a simple chemical vapor deposition accompanying with freeze drying strategy. The walnut-type structure noted as Si@Gra@Pc is obtained, in which the porous architecture not only shorten the transfer distance of the lithium ions but also provide good electrical conductivity for the charge carriers. Moreover, the porous structure permit the free expansion of Si during charging/discharging cycling and preserve the integrity of the electrode owing to the brawny mechanical strength of Gra and Pc framework. Importantly, it is found that the Si@Gra@Pc composites show good rate capability reached to 5Ag-1 with specific capacity of 450 mAh g-1 and good cycling stability with no distinct capacity decay even after 1000 cycles, which are obvious improving compared with that of the bare Si anodes. Combined with the simple and feasible fabrication method and improved electrochemical performance for the Si anodes in LIBs. The present walnut-type Si@Gra@Pc composite is considered as the promising and meaningful Si-based anode materials and candidates in the development of next-generation high specific energy LIBs.
Potent odorants of boiled potatoes

The potent odorants of boiled potatoes were screened by aroma extract dilution analysis, aroma extract concentration analysis, and gas chromatography-olfactometry of static headspace samples. Altogether 45 odorants were found of which 42 were identified, trans-4,5-Epoxy-(E)-2-decenal, methional, 2-acetyl-1-pyrroline, dimethyltrisulfide, 2,3-diethyl-5-methylpyrazine, vanillin, sotolon, decanal, (E,E)-2,4-nonadienal, (E,E)-2,4-decadienal, (E)-β-damascenone, furaneol, methanethiol, 3-isopropyl-2-methoxypyrazine, dimethylsulfide appeared in at least one of the three screening experiments with a higher flavour dilution factor.
Fast high‐resolution brain metabolite mapping on a clinical 3T MRI by accelerated [text removed]H‐FID‐MRSI and low‐rank constrained reconstruction

Correspondence Antoine Klauser PhD, CIBM—Radiology, University Hospitals of Geneva, CH‐1211 Geneva 14, Switzerland. Email: antoine.klauser@unige.ch Purpose: Epitomizing the advantages of ultra short echo time and no chemical shift displacement error, high‐resolution‐free induction decay magnetic resonance spectroscopic imaging (FID‐MRSI) sequences have proven to be highly effective in providing unbiased characterizations of metabolite distributions. However, its merits are often overshadowed in high‐resolution settings by reduced signal‐to‐noise ratios resulting from the smaller voxel volumes procured by extensive phase encoding and the related acquisition times. Methods: To address these limitations, we here propose an acquisition and reconstruction scheme that offers both implicit dataset denoising and acquisition acceleration. Specifically, a slice selective high‐resolution FID‐MRSI sequence was implemented. Spectroscopic datasets were processed to remove fat contamination, and then reconstructed using a total generalized variation (TGV) regularized low‐ rank model. We further measured reconstruction performance for random undersampled data to assess feasibility of a compressed‐sensing SENSE acceleration scheme. Performance of the lipid suppression was assessed using an ad hoc phantom, while that of the low‐rank TGV reconstruction model was benchmarked using simulated MRSI data. To assess real‐world performance, 2D FID‐MRSI acquisitions of the brain in healthy volunteers were reconstructed using the proposed framework. Results: Results from the phantom and simulated data demonstrate that skull lipid contamination is effectively removed and that data reconstruction quality is improved with the low‐rank TGV model. Also, we demonstrated that the presented acquisition and reconstruction methods are compatible with a compressed‐sensing SENSE acceleration scheme. Conclusions: An original reconstruction pipeline for 2D 1H‐FID‐MRSI datasets was presented that places high‐resolution metabolite mapping on 3T MR scanners within clinically feasible limits.
Peony: An integrated InfoVis design and development platform

We describe an integrated Information Visualization (InfoVis) development platform called Peony. Rather than being a low level InfoVis development toolkit, it is targeted at the full range of In-foVis users, including the InfoVis application designers from various application domains, the InfoVis component designers, and the professional InfoVis algorithm designers. Various interaction techniques and algorithms are supported in different separable modules, making it easy to build different visualizations by composing them in different ways. Peony’s high performance design enables it to handle huge datasets efﬁciently and we ran a number of performance tests to compare it to existing libraries. The core of the Peony platform has been implemented both in Java, as well as in ActionScript to facilitate web deployment. CR Categories: I.3. 6 [Methodology and Techniques]: Graphics data structures and data types; H.5 [User Interfaces]: Graphical User Interface, Benchmarking; C.4 [Performance of Systems]: Design Studies
Social Sites Mental Disorders Detection via Online Social Media Mining using Machine Learning Framework

: Development in social network communication encourages dangerous use. An increasing number of mental disorders in social networks, such as cybernetic dependency, information overload and network constraint, have recently been observed. Currently, the symptoms of these mental illness are passively observed, which causes late clinical intervention. In this paper, we argue that online social behaviour mining offers the chance to effectively recognize mental disorder at a beginning period. It is difficult to detect disorder because the mental state cannot be observed directly from the registers of online social activities. Our new and innovative approach to the act of disorder detection is not based on self-disclosure of these mental factors through psychology questionnaires. Instead, we propose a framework of machine learning or the detection of mental disorders in social networks, which exploits the features extracted from social network data to accurately identify possible disorder cases. We also use multiple learning sources in social network mental disorder and propose a new mental disorder based model to improve accuracy. Our framework is evaluated through a user study with none of the users on the network. We performed an analysis of the characteristics and we also applied the new proposed approach in large-scale data series and analysed the characteristics of the three types of mental disorder.
High Dimensional Markov Chain Monte Carlo with Multiple GPUs

Allocating computation over multiple threads to reduce running time has become a key to training big models such as deep neural networks because a Graphics Processing Unit (GPU), which is parallel in nature, can speed up intensive matrix operations. We present a new MCMC algorithm that can be distributed over multiple GPUs by combining bridge sampling with Hamiltonian Monte Carlo on partitioned sample spaces. We empirically show that this approach can expedite MCMC sampling for any unnormalized target distribution such as Bayesian Neural Network in a high dimensional setting. Furthermore, in the presence of multimodality, this algorithm is expected to be more e ﬃ - cient in mixing MCMC chains when proper partitions are chosen. Finally, by comparing the parameter distributions of di ﬀ erent learning method, we suggest that further studies could be conducted on the e ﬀ ect of a constrained sample space on the generalization error.
Development of microsatellite markers for the critically endangered Limonium dufourii (Girard) Kuntze (Plumbaginaceae)

Limonium dufourii is an endemic plant from the eastern Mediterranean coast of Spain with a triploid chromosome number and apomictic reproduction. We have isolated and characterized 13 polymorphic microsatellite loci from an enriched library in order to investigate its population genetic structure. Simple sequence repeat (SSR) loci were screened in 120 individuals from the six extant populations of this species. They show an average of 5.76 alleles per locus, ranging from 2 to 18, with seven loci exhibiting heterozygosities larger than 0.60. Three loci present one single allele in each individual, whereas one locus presents three alleles in every individual analysed.
Mineral Element Content of Some Benthic Marine Algae of the Kenya Coast

Introduction There i s abundant information on the mineral eleraent content of natural waters, but relatively few analyses have been made on the elemental content of the marine algae themselves. The investigations which have been carried out on the mineral element content of marine phytoplankton indicate that these algae can accumulate certain mineral elements against a concentration gradient (MOORE, 1958). YENTSCH (1962) has listed Ca, K, B, Mg and S äs the mineral elements found in excess for normal requirements. O£ the macroelements, nitrogen and phosphorus have been studied thoroughly and are now generally considered to be limiting for algal growth and development Other investigators have concerned themselves with the seasonal Variation in the mineral element content of marine phytoplankton, The literature surveyed indicated that more analyses of this nature have been made on species which inhabit the temperate waters rather than tropical waters (AiiciNS, 1930; MACPHERSON & YOUNG, 1952; WORT, 1955; YOUNG and LANGILLE, 1958). Recently ISAÄC and ISAAC (1967, 1968) published work on the taxonomy and ecology of marine algae and angiosperms of the Kenya Coast. The objective of this investigation was therefore to determine the mineral element composition of the more common species found at the Kenya Coast. In this paper, the results of five elements (Nitrogen, Phosphorus, Potassium, Calcium and Magnesium) are discussed*
Haematotoxic and Genotoxic Potential of Penconazole and Copper Nanoparticles on Redbelly Tilapia (Tilapia Zillii)

The extensive use of fungicides in both conventional and nanoengineered forms poses a major health threat to aquatic organisms. Some of the most sensitive and valid biomonitoring parameters for assessment of aquaculture toxins are changes in haemato-genotoxic endpoints. Therefore, this study aimed to examine the effects of penconazole (PEN) and copper nanoparticle (Cu-NP) fungicides on haematological parameters and erythrocyte micronucleus (MN) and nuclear abnormalities (ENAs) formation in male and female of Tilapia zillii and to elucidate differences with respect to dose and sex. A total of 180 normal adult Tilapia zillii were allocated equally to five groups with three replicates of 12 fish. The control group received no treatment, the PEN (I) group was exposed to PEN at a dose of 0.8 μg/L, the PEN (II) group was exposed to PEN at a dose of 1.6 μg/L, the Cu-NP (I) group was exposed to Cu-NP at a dose of 7.5 mg/L, and the Cu-NP (II) group was exposed to Cu-NP at a dose of 15 mg/L. The results showed that PEN and Cu-NPs markedly reduced RBC counts; induced leucocytosis, thrombocytosis and lymphocytosis; and obviously increased the percentages of MNs and ENAs in a dose-dependent manner. Males and females exhibited differential sensitivity to PEN and Cu-NPs depending on the dose and type of exposure. These patterns of adverse effects on haematological variables and the results of MN tests can be used as references for investigation of the ecotoxicity of these fungicides in fish. Further studies are highly recommended to explore the possible contributory factors involved in the haemato-genotoxic effects of these aquatic contaminants.
Interferon-α resistance can be reversed by inhibition of IFN-α-induced COX-2 expression potentially via STAT1 activation in A549 cells

The current study demonstrates that COX-2 expression is positively regulated by IFN-alpha, which is mediated by activation of STAT1 in A549 cells. The IFN-alpha-induced COX-2 expression and STAT1 activation were markedly inhibited by the addition of curcumin to the IFN-alpha-pretreated cells. While IFN-alpha or COX-2 inhibitors alone did not result in growth inhibition of A549 cells, the combination of IFN-alpha and celecoxib or curcumin resulted in a significant growth inhibition of A549 cells, which was associated with down-regulation of CDK2, 4, and 6 and up-regulation of p27. We demonstrate that the expression of COX-2 was induced by IFN-alpha possibly via STAT1 activation in the A549 human non-small cell lung cancer cell line, which may partly account for its IFN-alpha resistance. The addition of curcumin or celecoxib to the IFN-alpha-pretreated A549 cells altered the IFN-alpha sensitivity of cell growth inhibition.
Unsupervised Brain Tumor Detection

Accurate and fast automatic detection of brain tumors in 3D MR neuroimages can significantly aid early diagnosis, surgical planning, and follow-up assessment. Primary and metastatic tumors, which present substantial challenges to both human and state-of-the-art brain tumor detection algorithms due to their diverse location and size, need to be carefully monitored. We present a fully automatic, unsupervised algorithm that can detect single and multiple tumors ranging in size from 3 to 28,079 mm. Using 20 clinical 3D MR scans containing 1 to as many as 15 tumors per scan, our proposed approach achieves an 87.84 95.30% detection rate and an average end-to-end running time of 4 minutes. In addition, 5 normal clinical 3D MR scans are evaluated quantitatively to demonstrate that our approach also has the potential to discriminate between suspicious and normal brains.
Occupancy and Habitat Associations of Four Species of Sciurids in Ponderosa Pine-Gambel Oak (Pinus ponderosa-Quercus gambelii) Forests in Northern Arizona

Abstract In ponderosa pine-Gambel oak (Pinus ponderosa-Quercus gambelii) forests of north-central Arizona, we examined occupancy and habitats of four species of sciurids (rock squirrel Spermophilus variegatus, golden-mantled ground squirrel S. lateralis, gray-collared chipmunk Tamias cinereicollis, cliff chipmunk T. dorsalis). Numbers of captures were highly variable, suggesting a patchy distribution of species. All four species co-occurred on only one of the study sites. Gray-collared chipmunks and golden-mantled ground squirrels were relatively common on one site only. Golden-mantled ground squirrels were associated with mature forests with high canopy cover and low basal area, whereas gray-collared chipmunks were in locations with large numbers of logs and shallow litter. The two species of chipmunks appeared to be separated in space; gray-collared chipmunks were more common where cliff chipmunks were least common. Rock squirrels were relatively ubiquitous. There was evidence for an association of rock squirrels with increasing rocky cover and decreasing canopy cover, whereas cliff chipmunks occupied rocky areas with high canopy cover and numerous shrubs.
Evaluation of marking European silver eels with visible implant elastomer tags and alcian blue

After 183 days, the retention of the visible implant elastomer marks implanted on the belly and along the basis of the ventral fin margin of the European silver eel Anguilla anguilla was 100%. The retention of the alcian blue spots on the belly was 84% after 1 day, but decreased to 68% by the end of the experiment (after 183 days). Marking-induced mortality was 0% for both marking types over the complete trial period.
Multi Tissue Modelling of Diffusion MRI Signal Reveals Volume Fraction Bias

This paper highlights a systematic bias in white matter tissue microstructure modelling via diffusion MRI that is due to the common, yet inaccurate, assumption that all brain tissues have a similar T2 response. We show that the concept of “signal fraction” is more appropriate to describe what have always been referred to as “volume fraction”. This dichotomy is described from the theoretical point of view by analysing the mathematical formulation of the diffusion MRI signal. We propose a generalized multi tissue modelling framework that allows to compute the actual volume fractions. The Dmipy implementation of this framework is then used to verify the presence of this bias in two classical tissue microstructure models computed on two subjects from the Human Connectome Project database. The proposed paradigm shift exposes the research field of brain tissue microstructure estimation to the necessity of a systematic review of the results obtained in the past that takes into account the difference between the concepts of volume fraction and signal fraction.
Robust Stabilization of Nonlinear Fractional Order Interconnected Systems Based on T-S Fuzzy Model

This paper concerns robust stabilization of nonlinear fractional order interconnected systems. Based on uncertain fractional order Takagi–Sugeno fuzzy model and the fractional order extension of lyapunov direct method, a parallel distributed compensate controller is designed to asymptotically stabilize the fractional order interconnected systems. Then, a sufficient condition is given in the format of linear matrix inequalities. Simulation example is given to validate the effectiveness of the approach.
FLOCCULATION PROPERTY OF NEW WATER-SOLUBLE CELLULOSE- ACRYLAMIDE DERIVATIVES ELABORATED IN ALKALI MEDIUM

In the last few years, science and technology have made remarkable discoveries in the field of bio-renewable materials. In this context, polysaccharide based biopolymers present themselves as a high potential source of innovation. Due to its availability and biodegradability, Cellulose, the polymer belonging to the polysaccharide family, has a great interest today. Indeed, it is considered to be one of the most common organic polymers and an almost eternal source of raw material for the growing demand of eco-friendly materials. The objective of this work is to propose the elaboration of new water-soluble cellulose-acrylamide derivatives destined to the application as new bio-based flocculants for colloidal solution of Fe(OH)3. However, the new cellulose based floculants, cellulose acrylamide (Cac) and hydroxyethyl cellulose acrylamide (HECac), were elaborated in alkali medium. Since, the structural characterization showed that the reached degree of the substitution (DS) is close to 0.6 and to 1.3 for Cac and HECac, respectively. In addition, the effect of the reaction time was studied, and the results showed that its prolongation affects strongly the flocculation properties of the polymers. Indeed, the saponified amide groups to the carboxylates have been achieved at most 50% when the time of the reaction exceeds 1.5 h. Moreover, the flocculation behavior of Cac and HECac indicates that the flocculation efficiency increased with increasing in the saponification rate, which indicating that the carboxylate form increases the surface negative charge density of the polymers, where the electrostatic interaction governs the flocculation phenomenon between water-soluble cellulose-acrylamide derivatives (Cac and HECac) and Fe(OH)3 colloidal solution.
A Survey on Recognition of Strike-Out Texts in Handwritten Documents

-----------------------------------------------------------------------***-------------------------------------------------------------------- Abstract – A lot of research work is done in the field of OCR during the last few decades. Complexity arises when it is handwritten and increases if noise exists as it is a barrier for the recognition. In this survey, as to resolve this issue in Kannada we investigate the various work done in the field of Recognition of strike-out text and removal of strike done in various other languages like English, Bengali, Devanagari etc. This survey is of 3 sections. Section 1 is about introduction. Section 2 has a brief explanation of all the research work done in this field and we compare the results of their research. In section 3, we conclude the survey.