Miracle-dz/UniFAR-FTUs huggingface dataset:
Establishment and Comparison of Juvenile Female Mouse Models of Nonalcoholic Fatty Liver Disease and Nonalcoholic Steatohepatitis

Experimental research has successfully established an adult offspring animal model of nonalcoholic fatty liver disease (NAFLD), but the female offspring model of NAFLD in young age has not been well characterized yet. The aim of this study was to present a direct comparison of the maternal versus postweaning female juvenile NAFLD and nonalcoholic steatohepatitis (NASH) animal models. Four different female mouse models were established and compared using different high-fat diet feeding (HF) strategies in maternal mice and their offspring. The models were non-HF maternal mice and HF offspring with high-high fat (C/HHF), non-HF maternal mice and HF offspring with low-high fat (C/LHF), HF maternal mice and offspring both with high-high fat (HHF/HHF), and HF maternal mice and offspring both with low-high fat (LHF/LHF). A female control group (C/C) was also established. The offspring mice were raised to the age of 8 weeks and then euthanized. Blood glucose levels, lipid profiles, liver function, and triglycerides/total cholesterol contents were examined. Hepatic morphology and superoxide anion levels were evaluated. The nicotinamide-adenine dinucleotide phosphate activity and related regulatory subunits protein expression in the liver tissue were also determined. Our data demonstrated that offspring fat intake contributed to the successful establishment of NAFLD and maternal-offspring fat intake contributed to the successful establishment of NASH in juvenile female mice. Offspring high-fat exposure might be associated with the development of NAFLD and maternal high-fat exposure might be associated with the development of NASH in juvenile female offspring. Higher calories from a fat diet program (both in maternal and offspring) are more prone to inducing liver injury in offspring. In addition, the combination of the aforementioned two factors could aggravate this process. Moreover, oxidative stress was prominent in the juvenile female mouse model of NAFLD/NASH, and the mechanism might be related to the activation of liver NADPH oxidase.
Identification of the Gene sxtA (Domains sxtA1 and sxtA4) in Mexican Strains of Gymnodinium catenatum (Dinophyceae) and Their Evolution

Saxitoxin (STX) and its analogs are a broad group of natural neurotoxic alkaloids, commonly known as paralytic shellfish toxins. SxtA is the initial gene in the biosynthesis of saxitoxin. It has been proposed that the genes for STX biosynthesis had a bacterial origin and were acquired in the dinoflagellates by a horizontal gene transfer (HGT). In Gymnodinium catenatum, the origin of the STX genes is not well established. In this paper, we sequenced sxtA gene (domains sxtA1 and sxtA4) and determined the gene copy number in the genome in four Mexican strains of G. catenatum. We compare them with sequences of G. catenatum, Pyrodinium bahamense, and Alexandrium spp. from other geographic regions, and non-toxic producing dinoflagellates. Amplifications were performed for domains sxtA1 and sxtA4 from strains of G. catenatum and the phylogenetic analyses was done by maximum likelihood and Bayesian inference. The copy number determination was carried out using qPCR. The phylogenetic tree of domain sxtA4 showed the formation of two clades where G. catenatum sequences separated from the Alexandrium/Pyrodinium clade. The domain sxtA1 formed a higher number of clades than sxtA4. Sequences of G. catenatum were grouped together with sequences of Alexandrium. Dinoflagellates sequences that do not produce saxitoxin formed a separate clade. The gene copy number was 64 ± 30 and 110 ± 50 copies of sxtA1 and sxtA4 respectively. The identification of the gene sxtA of G. catenatum shows that the sequences are similar to those of Alexandrium species with low variations between species. These results may indicate that the acquisition of the gene sxtA was an early HGT event in the evolution of dinoflagellates. The possible loss of the ability to produce STX in some species suggests that the HGT from Alexandrium species towards G. catenatum is not possible.
Research on pedestrian detection technology based on improved DPM model

Pedestrian detection plays an important role in unmanned technology. Because of the high efficiency and robustness of the deformable part model, it has been widely applied to the field of pedestrian detection. At present, how to effectively reduce the risk of partial screening of pedestrians has been based on the pattern recognition of pedestrian detection technology in the hot spots. Aiming at this problem, after analyzing the deformable part model deeply, this paper creatively proposes a pedestrian detection method with improved deformable part model. By training the two-pedestrian deformable part model, the method is adopted to reduce the pedestrian detection in the pedestrian detection by matching the image sub-region and matching the matching result. It is shown that the method can improve the detection efficiency while ensuring the detection efficiency, while ensuring the effectiveness of the whole algorithm to meet the real-time requirements of unmanned technology.
Enumerating Minimal Transversals of Hypergraphs without Small Holes

We give a polynomial delay algorithm for enumerating the minimal transversals of hypergraphs without induced cycles of length 3 and 4. As a corollary, we can enumerate, with polynomial delay, the vertices of any polyhedron P(A, 1 ̄ ) = {x ∈ R | Ax ≥ 1 ̄ , x ≥ 0 ̄ }, when A is a balanced matrix that does not contain as a submatrix the incidence matrix of a cycle of length 4. Other consequences are a polynomial delay algorithm for enumerating the minimal dominating sets of graphs of girth at least 9 and an incremental delay algorithm for enumerating all the minimal dominating sets of a bipartite graph without induced 6 and 8-cycles. 2012 ACM Subject Classification Mathematics of computing → Graph enumeration, Mathematics of computing → Graph algorithms, Theory of computation → Graph algorithms analysis
A Simultaneous Hand-Eye Calibration Method for Hybrid Eye-in-Hand/Eye-to-Hand System

A hybrid system with both eye-in-hand and eye-to-hand configurations is often necessary for autonomous exploring equipment, such as ROVs. In order to localize objects accurately and grasp them rapidly, the relationships among the robot base, the end effector, the fixed cameras, and the cameras mounted on the end effector should be calibrated in advance. To achieve these goals, a fast calibration method is proposed in this paper, which could calibrate the hybrid camera system simultaneously. Then the feasibility and robustness of the proposed calibration method are verified by comparing it to the classical two-step method through simulations with different noise levels.
A Rehabilitation Robot Arm Based on Electromyographic

A sEMG analysis method based on neural network is proposed, which is applied to the control of rehabilitation robot arm. In this study, the sEMG acquisition system is designed to amplify and filter the original sEM G signal, the output signal are converted into digital signal by the NI acquisition card and sent to computer, and the data are analysed and patterned. Finally, the results are employed to control the rehabilitation robot arm. Experiments show that the proposed method can reduce the training time, overcome the lack of traditional EMG prosthetic control, and easily to be used. Rehabilitation patients can directly choose a variety of different limb movements with multi-degree of freedom of the arm control.
Evaluation of Chemical Strategies for Improving the Stability and Oral Toxicity of Insecticidal Peptides

Spider venoms are a rich source of insecticidal peptide toxins. Their development as bioinsecticides has, however, been hampered due to concerns about potential lack of stability and oral bioactivity. We therefore systematically evaluated several synthetic strategies to increase the stability and oral potency of the potent insecticidal spider-venom peptide ω-HXTX-Hv1a (Hv1a). Selective chemical replacement of disulfide bridges with diselenide bonds and N- to C-terminal cyclization were anticipated to improve Hv1a resistance to proteolytic digestion, and thereby its activity when delivered orally. We found that native Hv1a is orally active in blowflies, but 91-fold less potent than when administered by injection. Introduction of a single diselenide bond had no effect on the susceptibility to scrambling or the oral activity of Hv1a. N- to C-terminal cyclization of the peptide backbone did not significantly improve the potency of Hv1a when injected into blowflies and it led to a significant decrease in oral activity. We show that this is likely due to a dramatically reduced rate of translocation of cyclic Hv1a across the insect midgut, highlighting the importance of testing bioavailability in addition to toxin stability.
Matrix Factorization Equals Efficient Co-occurrence Representation

Matrix factorization is a simple and effective solution to the recommendation problem. It has been extensively employed in the industry and has attracted much attention from the academia. However, it is unclear what the low-dimensional matrices represent. We show that matrix factorization can actually be seen as simultaneously calculating the eigenvectors of the user-user and item-item sample co-occurrence matrices. We then use insights from random matrix theory (RMT) to show that picking the top eigenvectors corresponds to removing sampling noise from user/item co-occurrence matrices. Therefore, the low-dimension matrices represent a reduced noise user and item co-occurrence space. We also analyze the structure of the top eigenvector and show that it corresponds to global effects and removing it results in less popular items being recommended. This increases the diversity of the items recommended without affecting the accuracy.
Resistance Analysis of a 3-Day Monotherapy Study with Glecaprevir or Pibrentasvir in Patients with Chronic Hepatitis C Virus Genotype 1 Infection

Glecaprevir (an NS3/4A protease inhibitor) and pibrentasvir (an NS5A inhibitor) are potent and pangenotypic hepatitis C virus (HCV) direct-acting antivirals. This report describes the baseline polymorphisms and treatment-emergent substitutions in NS3 or NS5A detected in samples from HCV genotype 1-infected patients receiving 3-day monotherapy of glecaprevir or pibrentasvir, respectively. None of the NS3 polymorphisms detected in the 47 baseline samples collected prior to glecaprevir monotherapy conferred reduced susceptibility to glecaprevir. The NS3 A156T substitution, which conferred resistance to glecaprevir but had low replication efficiency, emerged in one genotype 1a-infected patient among the 35 patients with available post-baseline sequence data. Baseline NS5A polymorphisms were detected in 12 of 40 patients prior to pibrentasvir monotherapy; most polymorphisms were single-position NS5A amino acid substitutions that did not confer resistance to pibrentasvir. Among the 19 patients with available post-baseline NS5A sequence data, 3 had treatment-emergent NS5A substitutions during pibrentasvir monotherapy. All treatment-emergent NS5A substitutions were linked multiple-position, almost exclusively double-position, substitutions that conferred resistance to pibrentasvir. Replicons engineered with these double-position substitutions had low replication efficiency. In conclusion, resistance-conferring substitutions emerged in a small number of genotype 1-infected patients during glecaprevir or pibrentasvir monotherapy; unlike other NS5A inhibitors, pibrentasvir did not select single-position NS5A substitutions during monotherapy.
Hyperspectral Image Classification With Deep Learning Models

Deep learning has achieved great successes in conventional computer vision tasks. In this paper, we exploit deep learning techniques to address the hyperspectral image classification problem. In contrast to conventional computer vision tasks that only examine the spatial context, our proposed method can exploit both spatial context and spectral correlation to enhance hyperspectral image classification. In particular, we advocate four new deep learning models, namely, 2-D convolutional neural network (2-D-CNN), 3-D-CNN, recurrent 2-D CNN (R-2-D-CNN), and recurrent 3-D-CNN (R-3-D-CNN) for hyperspectral image classification. We conducted rigorous experiments based on six publicly available data sets. Through a comparative evaluation with other state-of-the-art methods, our experimental results confirm the superiority of the proposed deep learning models, especially the R-3-D-CNN and the R-2-D-CNN deep learning models.
Study on Statistical Characteristics of Sea Clutter Based on Measured Data with Large Grazing Angle

This paper presents some theoretical models of sea clutter, including Rayleigh distribution, Weibull distribution, logarithmic normal distribution, K distribution and KK distribution, whose fits are tested with measured data in Ku-band, high resolution capabilities and large grazing angle conditions. The fitting effect of the five distribution methods is analyzed in this paper and the results show that the amplitude of sea clutter is close to Rayleigh distribution in the case of large grazing angle and tail of the amplitude distribution curve of the sea clutter in some distance units deviates from the Rayleigh distribution while the K and KK distributions can fit better.
Management of an Electric Vehicle Charging System Supported by RES and Storage Systems

It is predicted to the near future that electric vehicle (EV) charging systems will have an important impact on the electric infrastructures. Thus, in order to contribute to a sustainable world, the use of renewable energy sources (RES) will play an important role to generate the required energy to the EVs. However, in order to optimize the global electrical efficiency, the RES should be placed as near as possible to the EVs charging systems. On the other hand, to provide stability to the system, energy storage systems, such as batteries and supercapacitors should also be considered. Under this context, this paper presents an EV charging system supported by RES and a storage system (supercapacitors and batteries). It will be presented the management of the storage systems, as well, an overall controller to stabilize the DC voltage bus. Several modes of the charging system operation will be presented. It also be presented results of the overall system showing the effectiveness of the proposed algorithms.
Modelling and Research of High-Efficiency Converter for Energy Storage Systems

The following paperwork considers modelling and examination of a high-efficiency converter for charging applications in energy storage systems. The converter provides galvanic isolation between the charged storage elements and the supplying DC bus. The high efficiency is due to the circuit soft-switching operation, as well as, to the implementation of a synchronous rectifier as an output stage. Characteristics of the converter operation are obtained. The opportunities for charging current control and voltage balancing between the individual cells are investigated. The obtained simulation results are verified by experimental examinations.
Superior efficacy of neoadjuvant chemotherapy and radical cystectomy in cT3‐4aN0M0 compared to cT2N0M0 bladder cancer

In this study, we compared complete pathological downstaging (pCD, ≤(y)pT1N0) and overall survival (OS) in patients with cT2 versus cT3–4aN0M0 UC of the bladder undergoing radical cystectomy (RC) with or without neoadjuvant chemo‐ (NAC) or radiotherapy (NAR). A population‐based sample of 5,517 patients, who underwent upfront RC versus NAC + RC or NAR + RC for cT2‐4aN0M0 UC between 1995–2013, was identified from the Netherlands Cancer Registry. Data were retrieved from individual patient files and pathology reports. pCD‐rates were compared using Chi‐square tests and OS was estimated by Kaplan–Meier analyses. Multivariable analyses were conducted to determine odds (OR) and hazard ratios (HR) for pCD‐status and OS, respectively. We included 4,504 (82%) patients with cT2 and 1,013 (18%) with cT3–4a UC. Median follow‐up was 9.2 years. In cT2 UC, pCD‐rate was 25% after upfront RC versus 43% (p < 0.001) and 33% (p = 0.130) after NAC + RC and NAR + RC, respectively. In cT3–4a UC, pCD‐rate was 8% after upfront RC versus 37% (p < 0.001) and 16% (p = 0.281) after NAC + RC and NAR + RC, respectively. In cT2 UC, 5‐year OS was 57% and 51% for NAC + RC and upfront RC, respectively (p = 0.135), whereas in cT3–4a UC, 5‐year OS was 55% for NAC + RC versus 36% for upfront RC (p < 0.001). In multivariable analysis for OS, NAC was beneficial in cT3–4a UC (HR: 0.67, 95%CI 0.51–0.89) but not in cT2 UC (HR: 0.91, 95%CI 0.72–1.15). NAR did not influence OS. In conclusion, NAC + RC was associated with superior pCD compared to RC alone and NAR + RC. Superior OS for NAC + RC compared to RC alone was especially evident in cT3–4a disease.
High-Speed Electric Machine with a Speed of 1.2 million rpm

This paper presents the study of microsize high-speed electric machine with a speed of 1.2 million rpm with a power of 100–150 W. The topology of machine is a synchronous electric machine with permanent magnets. The design of the rotor was chosen and calculation of the mechanical strength of the rotor by the finite element method was made. The most suitable type of bearing supports was determined. Dependence of aerodynamic losses on frequency and on radius of the rotor was revealed. Materials of the stator magnetic core and the stator conductors were selected. Electric machine losses were calculated. To evaluate the efficiency of the developed computer models and the calculation algorithm, the experimental verification of the machine (the motor mode) with a rotation speed of 500,000 rpm and a power of 100 W was carried out. The discrepancy between the developed models and experimental data does not exceed 5-7%.
Selective Oxidation of Veratryl Alcohol over Au-Pd/Ce0.62Zr0.38O2 Catalysts Synthesized by Sol-Immobilization: Effect of Au:Pd Molar Ratio

The selective oxidation of veratryl alcohol (VA), a model compound of lignin, with oxygen molecules to produce veratraldehyde (VAld) was studied over monometallic Au, Pd, and bimetallic Au:Pd nanoparticles supported on a Ce0.62Zr0. 38O2 mixed oxide for the first time. These bimetallic Au-Pd catalysts with Au:Pd molar ratios from 0.4 to 4.3 were synthesized by the sol-immobilization method. Furthermore, all the catalysts were characterized by inductively coupled plasma-atomic emission spectroscopy (ICP-AES), N2 physisorption, X-ray photoelectron spectroscopy (XPS), scanning transmission electron microscopy-high angle annular dark field (STEM-HAADF) imaging, energy dispersive X-ray spectroscopy (EDXS), and temperature programmed reduction (TPR) techniques. A synergistic effect between gold and palladium was observed over all the bimetallic catalysts in a wide range of studied Au:Pd ratios. Remarkably, the optimum Au:Pd ratio for this reaction was 1.4 with a turnover frequency of almost six times larger than for the monometallic gold and palladium catalysts. Selectivity to veratraldehyde was higher than 99% for the monometallic Au, Pd, and all the bimetallic Au-Pd catalysts, and stayed constant during the reaction time.
Adaptive UKF Based Parameter Estimation of Compliant Man-Machine Dynamic Model for Lower Limb Rehabilitation Robot

For lower limb rehabilitation robot, the precise man-machine dynamics model is the basis for effective and reliable rehabilitation training. The traditional man-machine system dynamic model is a rigid body model with simplified link structure, which is difficult to realize man-machine synchronization movement without any interference, As well as, the safety of human motion cannot be guaranteed. To solve this problem, An adaptive UKF based parameter estimation of compliant man-machine dynamic model for lower limb rehabilitation robot is put forward. Firstly, according to the compliance of the human body movement, the human dynamic model described in the structure of “connecting rod parallel viscoelastic unit” is established based on the mechanism of human lower limb movement. In addition, the dynamic model of lower limb rehabilitation robot is established. Then, on this basis, the man-machine combined dynamics model is established according to the interaction relationship between human and the rehabilitation robot. Next, the parameters of man-machine dynamic model, which reflect the compliance of human movement, are estimated online by adaptive UKF algorithm. Finally, the compliant man-machine dynamic model is simulated and analyzed. The simulation results show that the adaptive UKF based parameter estimation of compliant man-machine dynamic model is scientific and reasonable.
Influence of Diabetes Mellitus on the Recovery Trajectories of Function, Strength, and Self‐Report Measures After Total Knee Arthroplasty

As the proportion of individuals with diabetes mellitus (DM) in the aging population and the number of total knee arthroplasties (TKAs) both continue to grow, understanding the outcomes for these patient populations is critical. The purpose of this study was to determine whether patients with and without DM differed in the recovery of 3 physical performance measures during the first 90 days following a TKA.
Lyophilization of Liposomal Formulations: Still Necessary, Still Challenging

Nowadays, the freeze-drying of liposome dispersions is still necessary to provide a solid dosage form intended for different routes of administration (i.e., parenteral, oral, nasal and/or pulmonary). However, after decades of studies the optimization of process conditions remains still challenging since the freezing and the dehydration destabilize the vesicle organization with the concomitant drug leakage. Starting from the thermal properties of phospholipids, this work reviews the main formulation and process parameters which can guarantee a product with suitable characteristics and increase the efficiency of the manufacturing process. In particular, an overview of the cryo- and/or lyo-protective mechanisms of several excipients and the possible use of co-solvent mixtures is provided. Attention is also focused on the imaging methods recently proposed to characterize the appearance of freeze-dried products and liposome dispersions upon reconstitution. The combination of such data would allow a better knowledge of the factors causing inter-vials variability in the attempt to improve the quality of the final medicinal product.
High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence

High-frequency oscillations (HFOs) in the electroencephalogram (EEG) are thought to be a promising marker for epileptogenicity. A number of automated detection algorithms have been developed for reliable analysis of invasively recorded HFOs. However, invasive recordings are not widely applicable since they bear risks and costs, and the harm of the surgical intervention of implantation needs to be weighted against the informational benefits of the invasive examination. In contrast, scalp EEG is widely available at low costs and does not bear any risks. However, the detection of HFOs on the scalp represents a challenge that was taken on so far mostly via visual detection. Visual detection of HFOs is, in turn, highly time-consuming and subjective. In this review, we discuss that automated detection algorithms for detection of HFOs on the scalp are highly warranted because the available algorithms were all developed for invasively recorded EEG and do not perform satisfactorily in scalp EEG because of the low signal-to-noise ratio and numerous artefacts as well as physiological activity that obscures the tiny phenomena in the high-frequency range.