Miracle-dz/UniFAR-FTUs huggingface dataset:
Alpha and Beta Diversity of Dustywings and Brown Lacewings (Neuroptera: Coniopterygidae, Hemerobiidae) in a Temperate Forest of Tlaxcala, Mexico

Abstract. — Neuropterans are beneficial insects being generalist predators during both larval and adult stages. In Mexico, 349 neuropteran species have been recorded, but only two species are known from the state of Tlaxcala. We conducted a faunistic study and analysis of diversity of Coniopterygidae and Hemerobiidae at two sites within the municipality of Nanacamilpa, Tlaxcala. We collected monthly samples for a year using Malaise traps, with some sporadic sampling with nets and light traps. We identified a total of 19 species (8 Coniopterygidae and 11 Hemerobiidae) of which 11 are new records for the state and five are new records for the country. One of the brown lacewing species collected was only recently described from the study area in the Transmexican Volcanic Belt. Coniopterygids and hemerobiids showed three abundance peaks through the one-year sampling period at Los Búfalos (LB) study site, while a less defined pattern of two apparent peaks was observed at the Piedra Canteada (PC) site. Results of true alpha diversity (order 0) based on the 14 observed species model an expected six more species in LB and one more in PC, while species accumulations curves predict three to four more species at both LB and PC with an additional year of sampling. The amount of similarity between the two localities was 0.69 as they share 12 of the 19 species recorded.
Characterisation of 11 Microsatellite DNA Markers from the Neotropic Cormorant (Phalacrocorax Brasilianus)

The advances of molecular techniques have increased the development of cost and time-effective libraries of molecular markers, such as microsatellites, which allow us to estimate genetic parameters in order to characterise species' population structures. The Neotropic Cormorant (Phalacrocorax brasilianus) is one of the most abundant and widespread seabirds from the American continent, being present in a wide range of habitats, however further information about genetic markers in this species is scarce. A total of 26 pairs of primers were synthesised and 22 microsatellites were amplified correctly; 11 of them were polymorphic. The number of alleles per locus ranged from three to seven with a mean of 4.6 per locus. Six loci showed significant departure from Hardy–Weinberg equilibrium. The microsatellite markers identified and characterised in the present study are the first set developed for P. brasilianus and will contribute to the genetic map, quantitative traits mapping, and phylogenetic analysis of this species.
On the zagreb indices of the line graphs of polyphenylene dendrimers

Abstract In predicting of their bioactivity and physicochemical properties of a chemical graph extremely important correlated with mathematical invariants in the topological indices. These topological indices are well-known in mathematical chemistry, drugs delivery, biology, gene therapy, nanotechnology and in other areas of applied sciences. In this paper, we study two families of Polyphenylene dendrimers, namely D1[n] and D2[n]. We also compute their topological indices, Zagreb indices and Zagreb coindices based on the concept of the line graphs. Furthermore, we analyze the results of these indices for graphs D1[n] and D2[n].
Effects of blade surface roughness on compressor performance and tonal noise emission in a marine diesel engine turbocharger

A numerical study was conducted to investigate the effects of blade surface roughness on compressor performance and tonal noise emission. The equivalent sand-grain roughness model was used to account for blade surface roughness, and a hybrid method that combines computational fluid dynamics and boundary element method was used to predict compressor performance and tonal noise. The numerical approach was validated against experimental data for a baseline compressor. Nine different cases with different blade surface roughness were studied in this paper, the global performance was analyzed under compressor design speed, and the tonal noise level was predicted under the design condition. The results indicate that compressor total-to-total pressure ratio and isentropic efficiency were gradually decreased with the increasing blade surface roughness. Besides, the blade total pressure loss coefficient and the efficiency loss coefficient were also increased. It was found that the reverse flow at the leading edge of compressor rotor blades reduced blade loading. The pressure fluctuation at the leading edge showed that the peak of pressure fluctuations increased as the blade surface roughness was increased. The sound pressure level at blade-passing frequency shows a significant change with variation in blade surface roughness, which results in an increased total noise level. Furthermore, it was shown that the blade surface roughness had nearly no influence on acoustic directivity, but the sound pressure level increased with the increase in roughness, especially at blade-passing frequency.
Deriving Daily Activity Schedules from Dynamic, Purpose-Dependent Origin–Destination Matrices

Emerging transport modeling approaches such as agent/activity-based modeling as well as the shift toward data-driven paradigm have stressed the need for high-quality travel behavior data at a disaggregate level. Despite the advances in personal mobility tracking and capturing, aggregate methods such as origin–destination (OD) matrices are still the most widespread means to organize and represent travel demand information. Nonetheless, traditional ODs cannot directly capture substantial elements which can considerably affect travel behavior (e.g., trip interdependency, trip chaining, etc.) therefore they are not the most suitable mean to facilitate relevant analysis. The currently presented framework alleviates this limitation by combining the individual trips present in multi-period, purpose-dependent OD matrices into sequences of trips originating and ending at users’ home location (i.e., tours). This is achieved by integrating graph-theoretical with combinatorial optimization concepts. A graph theory-based methodology is applied to first examine the spatiotemporal information in ODs and then identify all the plausible tours. Then the sequence of activities (i.e., daily activity schedule [DAS]) taking place during each diurnal tour is inferred based on the trip-purpose information contained in the original ODs. Finally, a combinatorial optimization routine identifies the optimum combination of DAS whose aggregated trips represent the total travel demand as observed in the OD matrices. The resulting DAS by the proposed estimation framework has proven to be of significant accuracy and provide valuable information in relation to the characteristics of the population’s travel behavior within the urban space environment. This information is particularly useful to mitigate against the upcoming challenges in the field of smart mobility management.
Exploratory Analysis of the Relationships between Congestion, Travel Time Reliability, and Freight-Related Performance Management Measures and Their Associativity with the Roadway Attributes

The purpose of this study is to investigate the performance management measures related to highway system reliability, freight, and traffic congestion in light of the federal rulemaking that establishes these performance measures. The study conducts an exploratory analysis to understand their inter-relationships and examines their (un)common underlying attributes to discover their associativity with each of the performance measures. In doing so several traffic and roadway related characteristics of each reporting segment of the National Highway System (NHS) of South Carolina were processed and modeled for the travel time reliability and peak hour excessive delay using generalized linear models with a log-link function. The results from the study indicate that the unreliable Interstate segments contributed to about 87% of the excessive delays on the entire Interstate. It was also found that more than half of the non-Interstate NHS segments that experienced excessive delay, were reliable and they contributed to approximately 52% of the entire peak hour excessive delay of the non-Interstate NHS. The results from the model indicate that the directional annual average daily traffic (AADT) and the urban areas are the two most important attributes positively associated with all three performance measures, while the number of through lanes was found to be negatively associated with all three performance measures. The length of the reporting segments was positively associated with the excessive delays but negatively associated with the travel time reliabilities. The percentage of single trucks was unique to the Interstate delays and positively associated.
Robust output tracking of nonlinear systems with transient improvement via funnel-based sliding mode control

This paper studies a new procedure for robust tracking of nonlinear systems. This procedure is based on the combination of the sliding mode control and the funnel control, which in addition to the robust performance of the closed-loop system in the face of model uncertainties and/or external disturbances also leads to improvement of the characteristics of the transient responses. Using funnel control and the appropriate choice of the funnel can affect the convergence rate and overshoot. In this regard, a theorem has been presented and the effective performances of the suggested controller have been guaranteed in various respects based on exact mathematical analysis. Simulations have also been carried out to illustrate the efficiency of the proposed approach and to verify the theoretical achievements of the paper despite model uncertainties and external disturbances.
Endothelial cell responses to thrombin and shear stress

Endothelial cells alter their morphology in response to a combination of chemical and mechanical signals. Both thrombin and shear stress have been reported to activate integrin receptors, calcium channels and downstream Rho GTPases. The aim of the investigation was to contribute in the understanding of the mechanisms involved in the transduction of these signals. Biochemistry and microscopy-based techniques were employed to study the contribution of focal adhesion proteins (FAK, Paxillin, Src). Both thrombin and shear stress altered the phosphorylation status of FAK. paxillin and Src and the response was more rapid under shear stress conditions. The patterns of phosphorylation followed by specific tyrosine residues were similar for the two responses, but shear stress responses were cell type and magnitude-dependent. Despite similarities in focal adhesion protein phosphorylation patterns, changes in cell morphology differed between thrombin- and shear stress-treated endothelial cells. It was found that, thrombin-induced morphological changes preceded its effects on the phosphorylation of FAK, Src and paxillin while the shear-stress-induced morphological adaptations followed changes in the phosphorylation status of these proteins. Thrombin induced increased activity of RhoA. not Racl, but, only in the shear stress response, was stress fibre formation associated with increased phosphorylation of myosin light chain protein. These results suggest that the two stimuli signal through distinct pathways leading to different morphological changes. The role of the calcium-dependent proteases calpain-1 and calpain-2 was investigated using calpain inhibitors and isoform specific siRNAs. It was found that calpains and specifically calpain-2 plays an important role in the regulation of focal adhesion turnover. Calpain-2 could thereby play a central role in both the thrombin and shear stress responses in endothelial cells.
Optimal Energy Speed Profile of Medium-Speed Maglev Trains Integrating the Power Supply System and Train Control System

As a new type of transportation serving the suburban passengers, the medium-speed maglev (MSM) is gradually becoming the focus of scholars. This paper addressess the speed profile optimization problem for MSM train operations by integrating the power supply system and train control system under various constraints. Unlike the model for optimizing the mechanical energy of the train, this approach aims at the lowest energy consumption of the substation for the MSM system. First, a speed profile optimization model for the MSM train is built by combining the mathematical control model of the long stator synchronous linear motor and dynamic equation of train, in which the stator current is the control variable. Next, a dedicated dynamic programming approach is proposed to solve the optimization model. The results of the numerical experiments show that the proposed model outperforms the model that only considers the train mechanical energy, and the energy consumption is reduced by 10.3% and 6.5% in the two case studies, respectively. Furthermore, the relationship between energy consumption and travel time is analyzed to reflect the optimal results of the proposed model limited to different fixed travel time.
Alterations of Lipid Metabolism in Cancer: Implications in Prognosis and Treatment

Cancer remains the second leading cause of mortality worldwide. In the course of this multistage and multifactorial disease, a set of alterations takes place, with genetic and environmental factors modulating tumorigenesis and disease progression. Metabolic alterations of tumors are well-recognized and are considered as one of the hallmarks of cancer. Cancer cells adapt their metabolic competences in order to efficiently supply their novel demands of energy to sustain cell proliferation and metastasis. At present, there is a growing interest in understanding the metabolic switch that occurs during tumorigenesis. Together with the Warburg effect and the increased glutaminolysis, lipid metabolism has emerged as essential for tumor development and progression. Indeed, several investigations have demonstrated the consequences of lipid metabolism alterations in cell migration, invasion, and angiogenesis, three basic steps occurring during metastasis. In addition, obesity and associated metabolic alterations have been shown to augment the risk of cancer and to worsen its prognosis. Consequently, an extensive collection of tumorigenic steps has been shown to be modulated by lipid metabolism, not only affecting the growth of primary tumors, but also mediating progression and metastasis. Besides, key enzymes involved in lipid-metabolic pathways have been associated with cancer survival and have been proposed as prognosis biomarkers of cancer. In this review, we will analyze the impact of obesity and related tumor microenviroment alterations as modifiable risk factors in cancer, focusing on the lipid alterations co-occurring during tumorigenesis. The value of precision technologies and its application to target lipid metabolism in cancer will also be discussed. The degree to which lipid alterations, together with current therapies and intake of specific dietary components, affect risk of cancer is now under investigation, and innovative therapeutic or preventive applications must be explored.
Barley Root Proteome and Metabolome in Response to Cytokinin and Abiotic Stimuli

Cytokinin is a phytohormone involved in the regulation of diverse developmental and physiological processes in plants. Its potential in biotechnology and for development of higher-yield and more resilient plants has been recognized, yet the molecular mechanisms behind its action are far from understood. In this report, the roots of barley seedlings were explored as a new source to reveal as yet unknown cytokinin-responsive proteins for crop improvement. Here we found significant differences reproducibly observed for 178 proteins, for which some of the revealed cytokinin-responsive pathways were confirmed in metabolome analysis, including alterations phenylpropanoid pathway, amino acid biosynthesis and ROS metabolism. Bioinformatics analysis indicated a significant overlap between cytokinin response and response to abiotic stress. This was confirmed by comparing proteome and metabolome profiles in response to drought, salinity or a period of temperature stress. The results illustrate complex abiotic stress response in the early development of model crop plant and confirm an extensive crosstalk between plant hormone cytokinin and response to temperature stimuli, water availability or salinity stress.
Registration of ‘Sequoia’ Hard Red Winter Wheat

Stand establishment and emergence from deep planting are important traits for winter wheat (Triticum aestivum L.) cultivars produced in the US Pacific Northwest. The objective of this research was to develop an adapted winter wheat cultivar with a long coleoptile and the ability to emerge well from deep planting conditions in the dryland (<300 mm annual precipitation) regions of Washington State. ‘Sequoia’ (Reg. No. CV-1125, PI 678966) hard red winter wheat was developed and released by the Agricultural Research Center of Washington State University. Sequoia was tested under the population designations 2J040720, 3J040720, 2J061383, 3J061383, 4J061383, and 5J061383 and experimental designation WA8180, which were assigned through progressive generations of advancement. Sequoia is a tall cultivar adapted to the low-precipitation, rainfed wheat production regions of Washington with excellent emergence from deep planting. Sequoia has high-temperature, adultplant resistance to stripe rust, average grain protein, high grain volume weight, high yield potential, and excellent enduse quality properties.
Correspondence between maturity date and molecular variations in a NAC transcription factor of diploid and polyploid Prunus species

The maturity date (MD) of Prunus stone fruit has been long known to be a quantitatively inherited trait. A NAC -type gene indicated as PpNAC1 (ppa008301m) has been found recently to be a strong candidate of a major gene influencing MD in peach. A 9-bp insertion in this gene resulted in earlier MD in two segregating peach populations. This study was carried out to test whether this mutation in the PpNAC1 gene can be used as a reliable functional marker for MD in a wide range of peach cultivars of various origins and phenotypic characters. A total of 125 peach cultivars were examined using a 3 × 3 custom chi-square contingency table according to their NAC genotype and MD (early, midseason, and late). Cramer's V equaled 0.478 and the Goodman-Kruskal index (l) was 0.37, indicating an extremely strong correlation between MD and NAC genotype. In addition, we determined 15 sequences from 10 cultivars of five Prunus species including peach, almond, apricot, sour cherry, and European plum with E-values ranging from 9e-88 to 2e-74, supporting their homology to PpNAC1 . A total of 69 single nucleotide polymorphisms and two insertion/deletions were detected in the coding region of the partial NAC domain sequences with three mutations putatively inducing nonconservative amino acid replacements and a nonsense mutation in specific alleles of early ripening apricot and sour cherry cultivars. The results are discussed with focus on the putative molecular mechanisms of mutations in the NAC genes, crop evolutionary perspectives, and the opportunities for designing cost-efficient markers to predict MD in Prunus breeding programs.
Mixture of Organophosphates Chronic Exposure and Pancreatic Dysregulations in Two Different Population Samples

Organophosphates (OP) are a major agrochemical. The application of OP pesticides is expected to increase multifold in the coming decades. The etiology of diabetic diseases is attributed to multiple factors including OP pesticide exposure. The present study investigates pancreatic dysregulation with respect to exocrine enzymes and diabesity in groups of Pakistani and Cameroonian people exposed to a mixture of OP pesticides. Nine hundred and four OP exposed individuals were enrolled for this cross-sectional study after due consent and approval from an ethical review committee. Pesticides' residues were measured by GC-MS spectrometry. Cholinergic enzymes were measured by Elman's method. Serum glucose, insulin, serum amylase, lipase, and triglyceride were measured by spectrophotometry and ELISA; HOMA-IR was determined in OP exposed and non-exposed participants. Stata 15 and R 3.2. 0 software were used for statistical analysis of the data. Malathion, chlorpyrifos, and parathion residues were evident in plasma samples. RBC-acetylcholinesterase was significantly depressed in OP exposed groups. In both population samples, investigated pancreatic functions were found to be statistically significantly more dysregulated than non-exposed. OP exposure indicated risk of diabetes and insulin, glycaemia, adiponectin, triglycerides, and TNF-α dysregulations. The study concludes that both OP exposed population groups exhibited a mixture of OP residues and pancreatic dysregulation, although the effect was more pronounced in the Cameroonian population. In addition, serum lipase has a positive correlation with OP exposure and diabetes and may be suggested as an alternate/additional diagnostic marker for diabesity under OP exposure. However, screening of other environmental co-factors with OP for pancreatic dysregulation is suggested.
Engrams of Fast Learning

Fast learning designates the behavioral and neuronal mechanisms underlying the acquisition of a long-term memory trace after a unique and brief experience. As such it is opposed to incremental, slower reinforcement or procedural learning requiring repetitive training. This learning process, found in most animal species, exists in a large spectrum of natural behaviors, such as one-shot associative, spatial, or perceptual learning, and is a core principle of human episodic memory. We review here the neuronal and synaptic long-term changes associated with fast learning in mammals and discuss some hypotheses related to their underlying mechanisms. We first describe the variety of behavioral paradigms used to test fast learning memories: those preferentially involve a single and brief (from few hundred milliseconds to few minutes) exposures to salient stimuli, sufficient to trigger a long-lasting memory trace and new adaptive responses. We then focus on neuronal activity patterns observed during fast learning and the emergence of long-term selective responses, before documenting the physiological correlates of fast learning. In the search for the engrams of fast learning, a growing body of evidence highlights long-term changes in gene expression, structural, intrinsic, and synaptic plasticities. Finally, we discuss the potential role of the sparse and bursting nature of neuronal activity observed during the fast learning, especially in the induction plasticity mechanisms leading to the rapid establishment of long-term synaptic modifications. We conclude with more theoretical perspectives on network dynamics that could enable fast learning, with an overview of some theoretical approaches in cognitive neuroscience and artificial intelligence.