Miracle-dz/UniFAR-FTUs huggingface dataset:
Unscented Kalman Filter for Low-Thrust Orbit Transfer Optimization

Based on Unscented Kalman Filter( UKF) parameter estimation,an algorithm for efficient low-thrust orbit transfer optimization with high accuracy is developed in this paper. Minimum-fuel orbit transfer problem is mainly discussed. First,the problem is formulated as a two-point boundary value problem by using the maximum principle. By setting the initial values of the costates as parameters to be estimated and the boundary values as desired observations,this problem is transformed into a parameter estimation problem,and then is solved by using unscented Kalman filter. The convergence of this algorithm is based on the theory of probability,so the derivation of the gradient matrixes required by traditional indirect methods is avoided. Moreover,the difficulty of guessing the initial values of the costates is overcome. Due to the similarity in problem construction,minimum-time orbit transfer problem can also be solved by using this algorithm. Numerical simulations demonstrate that the algorithm is simple,efficient,accurate and robust.
Flexural Properties of Lattices Fabricated with Planar and Curved Layered Fused Filament Fabrication

The use of curved layers in fused filament fabrication could lead to various advantages in surface finishing and mechanical properties. Here, the influence of three different structural and manufacturing parameters (volume fraction, raster arrangement, and the use of curved or planar layers) on the mechanical properties of lattice structures under three-point bending is studied. Two different raster arrangements were considered, i.e., those with rasters at planes parallel to the principal axes of the samples and those diagonally arranged, all at four different volume fractions. All different samples were additively manufactured using planar and curved layers. Samples were further dimensionally inspected to refine the computational models before their analysis via finite element simulations. The linear elastic region of the load-displacement curves was further analyzed numerically via finite element models. Predictions with finite element models resulted in good agreement with errors below 10%. Samples with diagonal rasters were 70% softer than those parallel to the principal axes.
Secondary air induced flow structures and mixing in a fixed bed combustor

Air staging features widely in biomass combustion from small space heaters to industrial-scale moving grate systems. Whilst studies have been conducted into the impact of air staging on emissions and combustion performance, there is little or no insight into the exact flow dynamic and physical mechanisms that are induced by secondary air under such conditions. This paper uses experimental data to validate numerical predictions before investigating the flow field structures and mixing characteristics in a fixed bed air staged combustor. The study utilizes Constant Temperature Anemometry (CTA) experiments to establish boundary conditions for a lab-scale fixed bed combustor. Results from numerical simulations obtained using k − k l-𝜔 model were in good agreement with experimental data. Conditions tested cover five different secondary to total air ratios (Qs/Qt) and two different locations of secondary air injection. Results show that at Qs/Qt = 0.50, 0.25 and 0.18 one strong recirculation zone is induced upstream of the secondary air injection and one downstream. Varying the point of injection of secondary air from h/D = 0.64 to h/D = 0.40 also had an effect on the size of the upstream recirculation zone. Qs/Qt = 0.50 had the highest values of mixing index among all spatially located planes at the upstream of secondary air injection. The overall findings shed light on the possible flow interactions between secondary air and the top layers of fuel bed. They also highlight the significance of secondary air on inducing both upstream and downstream flow structures.
STEP IN: Supporting Together Exercise and Play and Improving Nutrition; a Feasibility Study of Parent-Led Group Sessions and Fitness Trackers to Improve Family Healthy Lifestyle Behaviors in a Low-Income, Predominantly Black Population

Background: Pediatric obesity is prevalent and challenging to treat. Although family-centered behavioral management is the gold standard, many families face structural inequities to its access and efficacy. Identifying ways to manage pediatric obesity within primary care is needed. Methods: This feasibility study included three sequential trials of peer-led group sessions occurring biweekly or monthly between 3/2016 and 2/2017. Parent–child dyads were recruited from a large academic primary care clinic via mailed invitations, prioritizing patients living in local zip codes of historical disinvestment. Eligible patients were 6 to 12 years with a body mass index ≥85th percentile, with parent and child interest in making healthy lifestyle changes, and English speaking. Results: 27 dyads participated, 77% were non-Hispanic Black. Retention and attendance rates were highest in the initial four-session biweekly pilot (100%, 0 dropouts), high in the full six-session biweekly cohort (83%, 1 dropout), and moderate in the monthly cohort (62.7%, 4 dropouts). Families reported high satisfaction with the sessions (4.75/5). Qualitative comments suggested social connections had motivated behavior change in some families. Conclusion: Parent-led group sessions for pediatric weight management show promise in engaging families. A future large trial is needed to assess behavior change and anthropometric outcomes.
NOTE ON TIHE CES PRODUCTION FUNCTION

where F is any (differentiable) function and 6 is a constant. " The present note shows that the class of functions of the above form is coextensive with the class of functions which have linear expansion paths and constant elasticity of substitution but demonstrates the existence of constant elasticity of substitution production functions which do not belong to this class. The term production function is used to denote a function f(a, b) with the properties:
Gearbox compound fault diagnosis method based on deep adversarial graph convolution transfer learning network under low label ratios

Advancement in measurement techniques has dramatically contributed to the development of the modern manufacturing industry. As the primary fault causing unplanned downtime of mechanical equipment, gearbox compound faults are usually coupled by single faults with unequal severity and are difficult to obtain. In industrial scenarios, monitoring data for extreme operating conditions is not available in advance, and labeling samples is time-consuming and costly. However, current research on unseen compound fault diagnosis relies on numerous labeled samples to train the model, and few studies are conducted on transfer learning and unseen compound fault diagnosis under low label ratios. To address the issue, a gearbox compound fault diagnosis method based on deep adversarial graph convolution transfer learning network (DAGCTLN) under low label ratios is proposed. Specifically, a novel DAGCTLN model, including a feature extractor, two label classifiers, and a discriminator, is constructed to realize the diagnosis of faults in the transfer domain and unseen compound faults in the source and target domains. The feature extractor of a three-layer graph convolutional network is presented to achieve deep extraction of fault features under low label ratios. Then a domain space adversarial mechanism between the feature extractor and discriminator is used to achieve global alignment of the source and target domain features. Furthermore, two label classifiers are constructed, and the adversarial adaptation of the decision boundary is realized by maxi-min the classifier difference to achieve subdomain alignment of the same class features in all domains. Experimental results indicate that DAGCTLN can achieve the highest fault diagnosis accuracy in the transfer domain compared to state-of-the-art algorithms. The average diagnosis accuracy of compound faults in all domains can reach 98.41% even if the label ratio is only 0.1, which provides guiding significance for the safe operation and predictive maintenance of mechanical equipment.
Evaluation of Plasma Lipocalin-2 as a Predictor of Etiology and Severity in Adult Patients with Community-Acquired Pneumonia

The aim of this study was to evaluate the diagnostic performance of plasma Lipocalin-2 (LCN2) concentration in adult patients with community-acquired pneumonia (CAP) to determine its etiology, severity and prognosis. A prospective observational study involving adults with CAP from November 2015 to May 2017 was conducted. Plasma LCN2 concentration was measured upon admission by a modified enzyme immunoassay coupled with chemiluminescence (Architect, Abbott Laboratories). The diagnostic performance of LCN2, C-reactive protein (CRP) and white blood cell to predict bacterial CAP was assessed. A total of 130 patients with CAP were included: 71 (54.6%) bacterial CAP, 42 (32.3%) unknown origin CAP and 17 (13.1%) viral CAP. LCN2 was higher in bacterial CAP than in non-bacterial CAP (122.0 vs. 89.7 ng/mL, respectively) (p = 0.03) with a limited ability to distinguish bacterial and non-bacterial CAP (AUROC: 0.62 [95% CI 0.52–0.72]). The LCN2 cutoff ≥ 204 ng/mL predicted the presence of pneumococcal bacteremia with an AUROC of 0.74 (sensitivity 70%, specificity 79.1%). Regarding severity, as defined by CURB-65 and PSI scores, there was a significant linear trend in the mean concentration of LCN2, exhibiting a shift from the low-risk to the intermediate-risk and high-risk group (p < 0.001 and 0.001, respectively). LCN2 concentration was associated with severity in adult patients with CAP. However, its utility as a biomarker to discriminate viral and bacterial etiology in CAP is limited.
Infrared Cirrus Detection Using Non-Convex Rank Surrogates for Spatial-Temporal Tensor

Infrared small target detection (ISTD) plays a significant role in earth observation infrared systems. However, some high reflection areas have a grayscale similar to the target, which will cause a false alarm in the earth observation infrared system. For the sake of raising the detection accuracy, we proposed a cirrus detection measure based on low-rank sparse decomposition as a supplementary method. To better detect cirrus that may be sparsely insufficient in a single frame image, the method treats the cirrus sequence image with time continuity as a tensor, then uses the visual saliency of the image to divide the image into a cirrus region and a cirrus-free region. Considering that the classical tensor rank surrogate cannot approximate the tensor rank very well, we used a non-convex tensor rank surrogate based on the Laplace function for the spatial-temporal tensor (Lap-NRSSTT) to surrogate the tensor rank. In an effort to compute the proposed model, we used a high-efficiency optimization approach on the basis of alternating the direction method of multipliers (ADMM). Finally, final detection results were obtained by the reconstructed cirrus images with a set threshold segmentation. Results indicate that the proposed scheme achieves better detection capabilities and higher accuracy than other measures based on optimization in some complex scenarios.
Application of Atmospheric-Pressure Plasma Treatment in Anti-Hairfalling of Polyester–Cotton Fleece Knitted Fabrics

In this study, atmospheric-pressure plasma (APP) was used to modify the surface of polyester–cotton fleece knitted fabrics to improve their anti-hairfalling properties. A series of treated samples were obtained by changing the power of plasma and treatment time. Scanning electron microscopy (SEM) and the surface roughness results reveal that the APP treatment can increase the roughness of fibers. The withdraw force and hairiness length of fibers results indicate that increasing withdraw force and decreasing hairiness length of fabrics can reduce hairfalling of the fibers. The values of weight loss rate confirm APP-treated powers and times can influence anti-hairfalling properties of fabrics. In addition, the best APP-treated time and electric power for the anti-hairfalling properties of the treated fabrics are respectively 15 s and 1.0 kW. Under this condition, the anti-hairfalling properties of the treated fabrics are improved by 48.3%, the contact angle decreased by 39.7%, and the wicking height increased by 18.3% compared with the untreated fabrics. It is notable that APP treatment does not affect the handle and tensile properties of fabrics.
In Silico-Motivated Discovery of Novel Potent Glycogen Synthase-3 Inhibitors: 1-(Alkyl/arylamino)-3H-naphtho[1,2,3-de]quinoline-2,7-dione Identified as a Scaffold for Kinase Inhibitor Development

Glycogen synthase kinase-3 (GSK-3) isoforms α and β have diverse roles within cell biology, and have been linked with multiple diseases that include prominent CNS conditions such as Alzheimer’s disease and several psychiatric disorders. In this study, motivated by computation, we aimed to identify novel ATP-binding site inhibitors of GSK-3 with CNS-active potential. A ligand screening (docking) protocol against GSK-3β was first optimized, employing an active/decoy benchmarking set, with the final protocol selected based on statistical performance analysis. The optimized protocol involved pre-filtering of ligands using a three-point 3D-pharmacophore, followed by Glide-SP docking applying hinge region hydrogen bonding constraints. Using this approach, the Biogenic subset of the ZINC15 compound database was screened, focused on compounds with potential for CNS-activity. Twelve compounds (generation I) were selected for experimental validation using in vitro GSK-3β binding assays. Two hit compounds, 1 and 2, with 6-amino-7H-benzo[e]perimidin-7-one and 1-(phenylamino)-3H-naphtho[1,2,3-de]quinoline-2,7-dione type scaffolds were identified with IC50 values of 1.63 µM and 20.55 µM, respectively. Ten analogues of 2 (generation II) were selected for structure activity relationship (SAR) analysis and revealed four low micromolar inhibitors (<10 µM), with 19 (IC50 = 4.1 µM)~five times more potent than initial hit compound 2. Selectivity screening of low micromolar inhibitors 14 and 19 (comparing aryl- and alkyl-substituents) against 10 homologous kinases revealed unique selectivity profiles, with both compounds more potent against the GSK-3α isoform (IC50s~2 µM) and, additionally, inhibitors of PKBβ (IC50s < 25 µM). Compound 14 also inhibited ERK2 and 19, PKCγ, but generally good selectivity for GSK-3 isoforms over the other kinases was observed. The compounds had excellent predicted oral bioavailability and CNS-activity profiles, presenting promising candidates for future testing in cellular models of disease.
Warm Ischemia Induces Spatiotemporal Changes in Lysophosphatidylinositol That Affect Post-Reperfusion Injury in Normal and Steatotic Rat Livers

Warm ischemia-reperfusion injury is a prognostic factor for hepatectomy and liver transplantation. However, its underlying molecular mechanisms are unknown. This study aimed to elucidate these mechanisms and identify the predictive markers of post-reperfusion injury. Rats with normal livers were subjected to 70% hepatic warm ischemia for 15, 30, or 90 min, while those with steatotic livers were subjected to 70% hepatic warm ischemia for only 30 min. The liver and blood were sampled at the end of ischemia and 1, 6, and 24 h after reperfusion. The serum alanine aminotransferase (ALT) activity, Suzuki injury scores, and lipid peroxidation (LPO) products were evaluated. The ALT activity and Suzuki scores increased with ischemic duration and peaked at 1 and 6 h after reperfusion, respectively. Steatotic livers subjected to 30 min ischemia and normal livers subjected to 90 min ischemia showed comparable injury. A similar trend was observed for LPO products. Imaging mass spectrometry of normal livers revealed an increase in lysophosphatidylinositol (LPI (18:0)) and a concomitant decrease in phosphatidylinositol (PI (18:0/20:4)) in Zone 1 (central venous region) with increasing ischemic duration; they returned to their basal values after reperfusion. Similar changes were observed in steatotic livers. Hepatic warm ischemia time-dependent acceleration of PI (18:0/20:4) to LPI (18:0) conversion occurs initially in Zone 1 and is more pronounced in fatty livers. Thus, the LPI (18:0)/PI (18:0/20:4) ratio is a potential predictor of post-reperfusion injury.
Maximum Likelihood Estimation in the Multiplicative Intensity Model: A Survey

Summary The nonparametric multiplicative intensity model for simple point processes on the line is considered. By introducing a suitable topology on the space of all point process paths, a topological extension of the model is found, accommodating point processes with multiple points. In the extended model the maximum likelihood estimator is determined and shown to be interpretable in terms of a multiple point process. Finally, the maximum likelihood estimator and the Aalen estimator are compared. The results are illustrated by examples involving a model for Poisson processes, a model for censored survival data and the Cox regression model.
On Tuning of Two-Degree-of-Freedom PID Controllers with Consideration on Location of Disturbance Input

The tuning problem of two-degree-of-freedom PID (2DOF-PID) controllers is studied. The focus is placed on the effects of the location where the major disturbance enters into the plant. First, analysis is made about their effects on the response curves, and then the optimal 2DOF-PID parameters are recalculated assuming generalized location of the disturbance entrance using the two-step optimization method proposed by the authors in the previous report. The results are studied from the viewpoint of the overall performance and a guideline of parameter tuning is presented.
The miR-141/200c-STAT4 Axis Contributes to Leukemogenesis by Enhancing Cell Proliferation in T-PLL

Simple Summary T-prolymphocytic leukemia (T-PLL) is a rare and poor-prognostic mature T-cell leukemia. A better understanding of this chemotherapy-refractory disease is highly warranted to identify novel treatment strategies. We previously identified an elevated expression of the miR-141/200c cluster in T-PLL cells. Here, we show a pro-proliferative effect of miR-141/200c in mature T-cell lymphoma cell lines. We further characterize a miR-141/200c-driven transcriptome, entailing altered expression of genes involved in pathways regulating cell survival and differentiation. Among those, we identified STAT4 as a miR-141/200c target gene, with low STAT4 expression being associated with an immature phenotype of T-PLL cells and with shortened overall survival of T-PLL patients. Overall, we present an oncogenic miR-141/200c-STAT4 signaling route in T-PLL, demonstrating, for the first time, a role of non-protein-coding genes in the leukemogenesis of this devastating disease. Abstract T-prolymphocytic leukemia (T-PLL) is a rare and mature T-cell malignancy with characteristic chemotherapy-refractory behavior and a poor prognosis. Molecular concepts of disease development have been restricted to protein-coding genes. Recent global microRNA (miR) expression profiles revealed miR-141-3p and miR-200c-3p (miR-141/200c) as two of the highest differentially expressed miRs in T-PLL cells versus healthy donor-derived T cells. Furthermore, miR-141/200c expression separates T-PLL cases into two subgroups with high and low expression, respectively. Evaluating the potential pro-oncogenic function of miR-141/200c deregulation, we discovered accelerated proliferation and reduced stress-induced cell death induction upon stable miR-141/200c overexpression in mature T-cell leukemia/lymphoma lines. We further characterized a miR-141/200c-specific transcriptome involving the altered expression of genes associated with enhanced cell cycle transition, impaired DNA damage responses, and augmented survival signaling pathways. Among those genes, we identified STAT4 as a potential miR-141/200c target. Low STAT4 expression (in the absence of miR-141/200c upregulation) was associated with an immature phenotype of primary T-PLL cells as well as with a shortened overall survival of T-PLL patients. Overall, we demonstrate an aberrant miR-141/200c-STAT4 axis, showing for the first time the potential pathogenetic implications of a miR cluster, as well as of STAT4, in the leukemogenesis of this orphan disease.
Still counting: new records, nomenclatural notes, and three new species of Phaeogenini (Hymenoptera, Ichneumonidae, Ichneumoninae) from the Afrotropical region

A synthesis of the Phaeogenini occurring in the Afrotropical region is provided. Three species are newly described: Centeterichneumon nambi Dal Pos, Diller & Di Giovanni sp. nov. from Uganda, Chauvinia ganota Claridge sp. nov. from Kenya, and Kibalus nonnaritae Dal Pos & Di Giovanni sp. nov. from Uganda. Heterischnus mfongosi Rousse & van Noort, 2013 is newly recorded for Kenya and Tanzania and the male of the species is diagnosed for the first time. Also, the female of Arearia oxymoron Rousse & van Noort, 2013 is diagnosed for the first time from one of the paratype localities. Lusius tenuissimus (Heinrich, 1938) and Chauvinia nyanga Rousse & van Noort, 2013 are recorded for the first time for Uganda and Kenya, respectively. In addition, new localities are given for Chauvinia nitida (Heinrich, 1938), Heterischnus olsoufieffi (Heinrich, 1938) and Hoplophaeogenes curticornis Heinrich, 1938. A new combination, Nesostenodontus mkomazi (Rousse & van Noort, 2013) comb. nov., is proposed to accommodate Heterischnus mkomazi. An updated key to the Afrotropical genera of Phaeogenini and keys to the Afrotropical species of the genera Arearia Seyrig, Centeterichneumon Heinrich, Chauvinia Heinrich, Heterischnus Heinrich, Hoplophaeogenes Heinrich, Kibalus Rousse, van Noort & Diller, and Lusius Tosquinet are provided. Updated online Lucid keys to genera and species are available from http://www.waspweb. org.
Analyse post-Pareto en optimisation vectorielle stochastique et déterministe : étude théorique et algorithmes.

Cette these relate certains aspects lies a l'analyse post-Pareto issue de Problemes d'Optimisation Vectorielle Stochastique. Un probleme d'optimisation Vectorielle Stochastique consiste a optimiser l'esperance d'une fonction vectorielle aleatoire definie sur un ensemble arbitraire et a valeurs dans un espace sectoriel ordonne. L'ensemble des solutions de ce probleme (appele ensemble de Pareto) est compose des solutions admissibles qui assurent un certain equilibre entre les objectifs : il est impossible d'ameliorer la valeur d'un objectif sans deteriorer celle d'un autre. D'un point de vue technique, chaque solution de Pareto est acceptable. Nous nous posons alors le probleme de la selection de l'une d'entre elles : en supposant l'existence d'un decideur qui aurait son propre critere de decision, nous considerons le probleme post-Pareto Stochastique qui vise a minimiser cette fonctionnelle sur l'ensemble de Pareto associe a un Probleme d'Optimisation Vectorielle Stochastique.