Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrafast imaging of fuel sprays: development of optical diagnostics, image processing

L’atomisation du carburant joue un role tres important dans l’efficacite globale du moteur a combustion interne utilisant le Diesel. Ce travail se concentre sur le developpement d’outils de diagnostics optiques rapides pour l’etude de l’atomisation du combustible liquide, avec pour but de caracteriser les jets de carburant en proche sortie de l’injecteur. Dans un premier temps, les techniques d’imagerie classiques utilisant (i) un eclairage continu avec une camera a haute vitesse et (ii) un eclairage pulse ultra-court avec une camera CCD haute resolution sont examinees. L’utilisation d’un supercontinuum (SC) pour eclairer le jet est testee. On observe alors que les images de spray obtenues avec ce type d’eclairage sont presque exemptes de speckle, ce qui en ameliore considerablement la nettete. Une technique d’imagerie classique est ensuite appliquee a l’etude de la cavitation a l’interieur d’un injecteur transparent et une premiere approche de ce probleme est presentee. Dans la partie suivante de la these, la problematique de la reduction du bruit du a la diffusion multiple de la lumiere sur le jet de carburant est posee. Les avantages et les inconvenients d’un montage utilisant une porte optique a effet Kerr avec des faisceaux pompe et sonde non colineaires sont presentes. Une nouvelle approche avec des faisceaux pompe et sonde colineaires aboutissant a une resolution temporelle de 1 ps est proposee. Des images balistiques de sprays de carburant en proche sortie d’injecteur ayant une excellente resolution spatiale sont ainsi obtenues. La possibilite d’utiliser un eclairage de type SC avec une porte optique est egalement discutee. Les images de sprays realisees par ce montage montrent que l’on reduit le speckle tout en gardant une bonne resolution spatiale. Enfin, les proprietes polarimetriques du milieu Kerr utilise lorsqu’il est soumis au faisceau pompe sont caracterisees par la mesure de sa matrice de Mueller (MM). Les parametres de polarisation depolarisation, diattenuation et retardance sont alors quantifies par decomposition de la MM mesuree, en utilisant le formalisme de decomposition polaire.
NiS2/Reduced Graphene Oxide Nanocomposites for Efficient Dye-Sensitized Solar Cells

NiS2 nanoparticles and nanocomposites of NiS2 with reduced graphene oxide (NiS2@RGO) have been successfully prepared via a facile hydrothermal reaction of nickel ions and sulfur source in the absence or presence of graphene oxide. NiS2@RGO nanocomposites exhibit excellent electrocatalytic performance for reduction of triiodide, owing to the improved conductivity and positive synergetic effect between NiS2 and RGO. As a consequence, the dye-sensitized solar cell with the NiS2@RGO counter electrode (CE) produces a power conversion efficiency of 8.55%, which is higher than that (7.02%) for the DSSC with the NiS2 CE, higher than that (3.14%) for the DSSC with the RGO CE, and also higher than that (8.15%) for the DSSC with the reference Pt CE under the same conditions.
Large-scale whole-genome resequencing unravels the domestication history of Cannabis sativa

Genome analyses provide new insights into the global domestication history of Cannabis sativa and its two main cannabinoids. Cannabis sativa has long been an important source of fiber extracted from hemp and both medicinal and recreational drugs based on cannabinoid compounds. Here, we investigated its poorly known domestication history using whole-genome resequencing of 110 accessions from worldwide origins. We show that C. sativa was first domesticated in early Neolithic times in East Asia and that all current hemp and drug cultivars diverged from an ancestral gene pool currently represented by feral plants and landraces in China. We identified candidate genes associated with traits differentiating hemp and drug cultivars, including branching pattern and cellulose/lignin biosynthesis. We also found evidence for loss of function of genes involved in the synthesis of the two major biochemically competing cannabinoids during selection for increased fiber production or psychoactive properties. Our results provide a unique global view of the domestication of C. sativa and offer valuable genomic resources for ongoing functional and molecular breeding research.
An ancestral recombination graph of human, Neanderthal, and Denisovan genomes

A new heuristic ARG inference tool maps archaic hominin admixture and highlights genomic regions unique to modern humans. Many humans carry genes from Neanderthals, a legacy of past admixture. Existing methods detect this archaic hominin ancestry within human genomes using patterns of linkage disequilibrium or direct comparison to Neanderthal genomes. Each of these methods is limited in sensitivity and scalability. We describe a new ancestral recombination graph inference algorithm that scales to large genome-wide datasets and demonstrate its accuracy on real and simulated data. We then generate a genome-wide ancestral recombination graph including human and archaic hominin genomes. From this, we generate a map within human genomes of archaic ancestry and of genomic regions not shared with archaic hominins either by admixture or incomplete lineage sorting. We find that only 1.5 to 7% of the modern human genome is uniquely human. We also find evidence of multiple bursts of adaptive changes specific to modern humans within the past 600,000 years involving genes related to brain development and function.
Kinetic study of the crystallization process of the α-Fe phase in the amorphous Fe81B13Si4C2 alloy

The kinetic study of the crystallization process of the α-Fe phase from the amorphous Fe 81 B 13 Si 4 C 2 alloy was investigated by DSC and XRD techniques. The kinetic parameters (lnA, E a ) of the investigated process were determined using the Kissinger and isoconversional (model-free) methods. It was established that the α-Fe crystallization process can be described by the JMA (Johnson-Mehl-Avrami) kinetic equation. In accordance with the XRD analysis and the calculated crystallization parameters (n = 4; m = 3), it was concluded that the crystallization stages of the considered process can be described by the bulk nucleation and the three-dimensional (3D) growth of nuclei.
Development and characterization of healthy gummy jellies containing natural fruits

Abstract The reduction of sugar and the addition of healthier ingredients in gummy jellies brings some improved health characteristics to a product that usually is devoid of nutrition. Therefore, the aim of this study is to develop gummy jellies using natural ingredients, without added sugars or additives, in two varieties: one including orange juice and slightly sweetened with honey (ORH) and the other including puree made from a mixture of berries (BEM). These were submitted to physicochemical, microbiological, and sensorial analyses. Results of microbiological analyses showed that both gummies were suitable for consumption accordingly to EU legislation. The physicochemical analyses allowed making a nutritional evaluation, so that ORH and BEM presented 73.8 kcal/100 g and 39.8 kcal/100 g, respectively, five and nine times lower than similar commercial products. The contribution of macronutrients of ORH and BEM was as follows: 78.0 and 67% from carbohydrates, 21.7 and 33% from proteins, respectively. Regarding the potential functional properties, the antioxidant capacity was 50.4 ± 4.5 mg/L TE for ORH and 83.7 ± 7.6 mg/L for BEM. Sensorial evaluation showed that although the developed gummy jellies were slightly less appreciated than a commercial counterpart, still they were appreciated by members of a panel and particularly the ORH, which was rated with scores almost equal to those of the commercial sample. In addition, the developed gummies showed lower caloric values and higher antioxidant capacity than similar commercial candies. Overall, ORH and BEM gummy jellies could represent an opportunity to provide consumers with a healthier alternative to the common jelly candies available in the market.
Pfam domain adaptation profiles reflect plant species’ evolutionary history

The increase in global temperatures predicted by climate change models presents a serious problem for agriculture because high temperatures reduce crop yields. Protein biochemistry is at the core of plant heat stress response, and understanding the interactions between protein biochemistry and temperature will be key to developing heat-tolerant crop varieties. Current experimental studies of proteome-wide plant thermostability are limited by the complexity of plant proteomes: evaluating function for thousands of proteins across a variety of temperatures is simply not feasible with existing technologies. In this paper, we use homologous prokaryote sequences to predict plant Pfam temperature adaptation and gain insights into how thermostability varies across the proteome for three species: maize, Arabidopsis, and poplar. We find that patterns of Pfam domain adaptation across organelles are consistent and highly significant between species, with cytosolic proteins having the largest range of predicted Pfam stabilities and a long tail of highly-stable ribosomal proteins. Pfam adaptation in leaf and root organs varies between species, and maize root proteins have more low-temperature Pfam domains than do Arabidopsis or poplar root proteins. Both poplar and maize populations have an excess of low-temperature mutations in Pfam domains, but only the mutations identified in poplar accessions have a negative effect on Pfam temperature adaptation overall. These Pfam domain adaptation profiles provide insight into how different plant structures adapt to their surrounding environment and can help inform breeding or protein editing strategies to produce heat-tolerant crops.
Intake, performance, and feeding behavior of Holstein and Holstein x Gyr heifers grazing intensive managed tropical grasses during the rainy season

Holstein × Gyr and Holstein are the primary dairy breed used in tropical systems, but when rearing under pasture, feed intake, behavior, and performance might differ between them. This study aimed to evaluate the voluntary intake, nutrient digestibility, performance, and ingestive behavior of Holstein and Holstein × Gyr (½ Holstein × ½ Gyr) heifers managed in an intermittent grazing system of Guinea grass (Panicum maximum Jacq. cv. Mombaça). The experiment was conducted during the summer season throughout four periods of 21 d. Two 8-heifers (four Holstein and four Holstein × Gyr) groups, averaging 258.6 ± 24.8 kg and 157.1 ± 24.99 kg body weight, were used. Each group grazed a separate set of 16 paddocks, and all heifers received a concentrate supplement daily. Heifers were weighed at the beginning and end of the experiment. Fecal, forage and concentrate samples were evaluated for their dry matter (DM), crude protein (CP), crude fat, ash, neutral detergent fiber (NDF), and indigestible NDF. Feeding behavior was evaluated through 24 h of live observation for 48 h of each experimental period. Grazing, ruminating, resting, and intake of concentrate times were recorded, and rumination criteria, bout criteria, mealtime, meal frequency, and meal duration were estimated. There was no difference in dry matter intake (DMI). The Holstein × Gyr heifers had greater NDF intake and average daily gain (ADG), and feed efficiency tended to show greater CP and NDF digestibilities. The forage DMI of Holstein × Gyr was 11.70% greater than the Holstein heifers. Holstein grazed less than Holstein × Gyr heifers in the afternoon. Ruminating time was 18.43% lower for Holstein than Holstein × Gyr heifers, and rumination criteria were greater for Holstein heifers. Holstein heifers presented more prolonged rumination bouts and resting time than Holstein × Gyr heifers. Holstein × Gyr can ingest and ruminate greater amounts of fibrous material. Holstein heifers select lower fiber material, and they need to spend more time ruminating small portions of feed. Overall, we do not recommend using young Holstein heifers in tropical pasture conditions because their ADG is low because of its lower adaptability to fibrous feed and heat stress. However, this management condition is appropriate for Holstein × Gyr heifers and results in an adequate performance. Implications This study was the first to evaluate the performance and behavior of young Holstein × Gyr and Holsteins heifers in tropical grazing systems under the same nutritional and environmental conditions. Crossbreed and purebred heifers interacted differently with the pasture; however, without noticeable variation in grazing time. As expected, Holstein heifers’ performance in the tropical pasture was impaired by a reduction in intake and grazing time. The greater performance observed for Holstein × Gyr heifers was assigned to greater forage intake, rumination time, and efficient forage nutrient use, showing animal’s adaptability to management conditions.
hnRNPA1 regulates early translation to replication switch in SARS-CoV-2 life cycle

Our study suggests that methylation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is essential for its optimal replication in the target cells. Heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1, an RNA-binding protein) was shown to mediate deposition of N6-methyladenosine (m6A) in internal SARS-CoV-2 RNA. The levels of hNRNPA1 expression and extent of methylation varied, depending on the course of SARS-CoV-2 life cycle. The recruitment of eIF4E (translational initiation factor) facilitated viral RNA translation at 1 hour post infection (1 hpi). However, at 2 hpi, methylation of internal SARS-CoV-2 RNA recruited hNRNPA1 which facilitated viral RNA transcription but resulted in translational repression, a phenomenon contributing in understanding the early translation to replication switch in the viral life cycle. Besides, the abrogation of methylation also produced a defective 5’ cap of viral RNA which failed to interact with eIF4E, thereby resulting in a decreased synthesis of viral proteins. To conclude, methylation of the internal and 5’ cap of SARS-CoV-2 RNA was shown to regulate transcription and translation of SARS-CoV-2 in a time dependent manner. IMPORTANCE RNA modifications are found in all life forms and have been linked to development, health and diseases. Our study reveals that internal SARS-CoV-2 RNA methylation (m6A) is essential for interaction with hNRNPA1 to effectively synthesize viral genome. Besides, m6A-marked RNA and hRNPA1 interaction was also shown to regulate early translation to replication switch in SARS-CoV-2 life cycle. Blocking SARS-CoV-2 RNA methylation resulted in reduced virus yield, suggesting epitranscriptomic machinery (methylation) facilitates SARS-CoV-2 replication and might represent potential target for new antiviral drugs against COVID-19.
Candida auris is rendered non-viable by medium-chain fatty acids

The medium-chain fatty acids, octanoic and decanoic acid, found in coconut oil, were fungistatic and decanoic acid was fungicidal against a panel of Candida auris strains, during both planktonic and biofilm growth. The strains were from all four major geographic clades, and some were resistant to several classes of antifungal drugs. These compounds are safe, natural products and could provide a new strategy for skin decolonization and environmental decontamination.
Mathematically and biologically consistent framework for presence-absence pairwise indices

Aim Large number of indices for presence-absence data that compare two assemblages have been proposed or reinvented. Interpretation of these indices varies across the literature, despite efforts for clarification and unification. Most effort has focused on the mathematics behind the indices, their relationships with diversity, and between each other. At the same time, following issues have been largely overlooked: (i) inter-dependence of indices based on their informational value, (ii) overlap of the ecological phenomena that the indices aim to capture, (iii) requirement that a small re-arrangement of assemblages should only cause a small change in an index, and (iv) inferences from the indices about diversity patterns. Underappreciation of these issues has led to invention or reinvention of indices without increasing their information value. We offer a framework for pairwise diversity indices that accounts for these issues. Methods We present a framework that links different ecological phenomena to pairwise indices, and show mathematical links between the indices. We distinguish statistical dependence of indices from their informational (mathematical) dependence. Using linear algebra, we found the minimum number of indices needed to detect different patterns. Results We (1) classified existing indices into three major and four minor mutually independent families, (2) demonstrated how assemblage interrelation confuses conceptually different patterns, (3) showed what can be inferred about diversity phenomena from different indices, (4) demonstrated problems with most of the indices of nestedness, (5) provided formula linking mathematically (informationally) dependent indices, and (6) showed which combinations of indices can be used for meaningful ecological inference. Additionally, (7) we showed how to calculate any index from two presence-absence indices, which can be used to standardize and compare different indices across the literature. Main conclusions It is impossible to purify an index of a single biodiversity phenomenon from the effects of other phenomena, because phenomena inevitably bound each other (e.g. a species richness gradient bounds possible values of Jaccard index of community similarity). Consequently, inventing indices which seemingly purify these effects (e.g. pure turnover or nestedness) leads to misleading inference. In contrast, a proper inference is obtained by using a combination of classical indices from different, information-independent families.
Ribocutter: Cas9-mediated rRNA depletion from multiplexed Ribo-seq libraries

RNA sequencing libraries produced from fragmented RNA, especially Ribo-seq libraries, contain high proportions of reads from abundant non-coding RNAs. Here, we describe a streamlined Cas9-based protocol for removing abundant rRNA/ncRNA contaminants from Ribo-seq (or other small RNA-seq) libraries and an easy-to-use software tool, ribocutter, for designing ready-to-order sgRNA templates. Following sgRNA template design, the pool of templates is in vitro transcribed using a 1-step commercial kit, which produces enough sgRNAs for multiple treatments. A single multiplexed sequencing library is then treated with Cas9/sgRNAs, followed by a short PCR program, which can increase the fraction of useful reads by more than 3-fold. Comparison of samples before and after depletion demonstrates that Cas9 produces minimal off-target effects and preserves key features (eg. footprint length, periodicity) of Ribo-seq libraries. The method is thus highly effective, costs <£0.50 per sample, and minimises non-specific depletion and technical variation between samples.
Motor memories of object dynamics are categorically organized

The ability to predict the dynamics of objects, linking applied force to motion, underlies our capacity to perform many of the tasks we carry out on a daily basis. Thus, a fundamental question is how the dynamics of the myriad objects we interact with are organized in memory. Using a custom-built three-dimensional robotic interface that allowed us to simulate objects of varying appearance and weight, we examined how participants learned the weights of sets of objects that they repeatedly lifted. We find strong support for the novel hypothesis that motor memories of object dynamics are organized categorically, in terms of families, based on covariation in their visual and mechanical properties. A striking prediction of this hypothesis, supported by our findings and not predicted by standard associative map models, is that outlier objects with weights that deviate from the family-predicted weight will never be learned despite causing repeated lifting errors.
Twisting DNA by salt

The structure and properties of DNA depend on the environment, in particular the ion atmosphere. Here, we investigate how DNA twist -one of the central properties of DNA- changes with concentration and identity of the surrounding ions. To resolve how cations influence the helical twist, we combine single-molecule magnetic tweezer experiments and extensive all- atom molecular dynamics simulations. Two interconnected trends are observed for monovalent alkali and divalent alkaline earth cations. First, DNA twist increases monotonously with increasing concentration for all ions investigated. Second, for a given salt concentration, DNA twist strongly depends on cation identity. At 100 mM concentration, DNA twist increases as Ba2+ < Na+ < K+ < Rb+ < Li+ ≈ Cs+ < Sr2+ < Mg2+ < Ca2+. Our molecular dynamics simulations reveal that preferential binding of the cations to the DNA backbone or the nucleobases has opposing effects on DNA twist and provides the microscopic explanation of the observed ion specificity. However, the simulations also reveal shortcomings of existing force field parameters for Cs+ and Sr2+. The comprehensive view gained from our combined approach provides a foundation for understanding and predicting cation-induced structural changes both in nature and in DNA nanotechnology.
Transfer Learning With CNN for Classification of Weld Defect

Traditional Image Processing Techniques (IPT), used for automating the detection and classification of weld defects from radiography images, have their own limitations, which can be overcome by Deep Neural Networks (DNN). DNN produces considerably good results in fields which offer big dataset for it to train. DNN trained with small datasets by conventional methods produces less accurate results. This limits the use of DNN in many fields. This study focuses to overcome this limitation, by adopting transfer learning using Pre-trained deep convolutional neural networks. By this method, a weld defect radiographic image classifier, which can classify 14 types of weld defects, was constructed. 940 Image patches of weld defects were manually collected and labelled from GDXray database. Subsequently the features of this weld defect dataset were extracted using VGG16 and ResNet50 CNNs, both pre-trained on the ImageNet database. Then machine learning models such as Logistic Regression, Support Vector Machine (SVM) and Random Forest were trained on these extracted features. The Classifier based on SVM trained on features extracted by ResNet50 outperforms the other counter parts with an accuracy of 98%. In all these cases, transfer learning improves performance and reduces the training time and computational system requirements.
wbacon: Weighted BACON algorithms for multivariate outlier nomination (detection) and robust linear regression

Outlier nomination (detection) and robust regression are computationally hard problems. This is all the more true when the number of variables and observations grow rapidly. Among all candidate methods, the two BACON (blocked adaptive computationally efficient outlier nominators) algorithms of Billor et al. (2000) have favorable computational characteristics as they require only a few model evaluations irrespective of the sample size. This makes them popular algorithms for multivariate outlier nomination/detection and robust linear regression (at the time of writing Google Scholar reports more than 500 citations of the Billor et al. (2000) paper).