Miracle-dz/UniFAR-FTUs huggingface dataset:
The Peptide-Directed Lysosomal Degradation of CDK5 Exerts Therapeutic Effects against Stroke

The aberrant activation of CDK5 has been implicated in neuronal death in stroke. The goal of this study is to determine whether knocking down CDK5 by a peptide-directed lysosomal degradation approach is therapeutically effective against stroke. We synthesized a membrane-permeable peptide that specifically binds to CDK5 with a chaperone-mediated autophagy targeting motif (Tat-CDK5-CTM) and tested its therapeutic effects on a mouse model of ischemic stroke. Our results showed that Tat-CDK5-CTM blocked the CDK5-NR2B interaction, resulting in the degradation of CDK5, which in turn prevented calcium overload and neuronal death in cultured neurons. Tat-CDK5-CTM also reduced the infarction area and neuronal loss and improved the neurological functions in MCAO (Middle cerebral artery occlusion) mice. The peptide-directed lysosomal degradation of CDK5 is a promising therapeutic intervention for stroke.
Comment on the Communication “The Key to Solving the Protein‐Folding Problem Lies in an Accurate Description of the Denatured State” by van Gunsteren et al.

In a recent communication, [1] van Gunsteren et al. proposed that the folding of proteins is much easier than has been believed [2] because the number of accessible conformers in the denatured state is only on the order of 10 9 for a 100-residue protein, instead of on the order of 10 24 to 10 30 used in previous analyses. [3, 4] This would make it possible for a polypeptide chain to fold to the native state in about 1 s by a random search since the transition from one conformer to another requires about 1 ns. [5] Van Gunsteren et al. [1] based their argument on simulations ranging from 32 to 200 ns of the folding and unfolding of six b and a amino-acid peptides in methanol and water. For these peptides, the number of conformers found by them corresponds to 1.22 to 1.74 con-formers per torsional degree of freedom, in the same range as the value 1.33 we found [6] in Monte Carlo simulations with an implicit solvent model of a denatured 16-residue peptide that forms a b-hairpin in the folded state; the simple average of the number of conformers per torsion angle calculated by van Gunsteren et al. for the different peptides is 1.40. If the number of conformers scales exponentially with the number of amino acids, an estimate of 1.33 (1.40) conformers per backbone torsion angle leads to a denatured state for a 100-residue protein with 1.33 200 (1.40 200)  6 Â 10 24 (1.7 Â 10 29) accessible conformers, [3, 4] which is many orders of magnitude larger than the value (10 9) suggested by van Gunsteren et al. The essential question concerns not the number of conformers observed in the peptide studies, but the statement that the number of conformers ™does not grow exponentially with the length of the peptide∫ [p. 364/352 of ref. [1]]. It is the latter that leads to their optimistic conclusion concerning the simplicity of the protein folding problem. There is no evidence for or against this claim in their simulations. The peptides studied vary by only a factor of two in size; in fact, there is one short peptide (9 torsion angles) and the five others vary in length only between 16 and 21 torsion angles. Since the number of conformers shows essentially no correlation with the number of torsion angles (the Pearson linear correlation coefficient between the …
Benchmarking of Industrial Synthetic Graphite Grades, Carbon Felt, and Carbon Cloth as Cost-Efficient Bioanode Materials for Domestic Wastewater Fed Microbial Electrolysis Cells

Anode material selection is crucial when it comes to building up-scaled microbialelectrolysis cells (MEC), as it has a huge influence on the achievable current density and account for a large part of the MEC total investment cost. Graphite is a material that isperfectly suited to the creation of up-scaled bioanodes as it is conductive, chemically stable, biocompatible, and relatively cheap but there are a very large number of commercially available grades of industrial graphite. In this study, five grades of industrial synthetic graphite (named G1–G5) were bench tested to select the most suitable gradefor future development of 3D bioanode for domestic wastewater (dWW) fed MEC application. The five grades of graphite have been selected with similar physico-chemicaland surface properties (electrical resistivity, surface roughness, and hydrophobicity) theoretically appropriate for EA biofilm development. Nevertheless, significant current density disparities where observed with the five graphite grades, which can certainlybe explained by the fabrication procedures of the respective material grades. With thegraphite grade giving the most efficient anodes (G3), an average steady state currentdensity of 2.3 A/m²was produced, outperforming the other grades by at least 15%. Even though all graphites had very close physico-chemical characteristics, the gradehad a clear significant influence on the current densities produced. G3 graphite was finally compared to carbon felt (CF) and carbon cloth (CC) both in terms of bio-electrochemicalcurrent production and bacterial communities colonizing electrodes. G3 bioanodes outperformed CF and CC bioanodes by 50% in term of steady state current density.Biofilms microbial population analysis showed that theGeobacterspecies was presentat 82% on G3 bioanodes, 39% on CF bioanodes, and 61% on CC bioanodes when it was only present at 0.06% in the activated sludge used as inoculum. This significant difference in bacterial enrichment could come from the huge gap between materials resistivity, as graphite resistivity is 200-fold lower than CF and CC resistivities. The strongly hydrophilic surface of G3 graphite was also certainly beneficial for biofilm development compared tothe hydrophobic surfaces of CF and CC.
EEG-Based Classification of Internally- and Externally-Directed Attention in an Augmented Reality Paradigm

One problem faced in the design of Augmented Reality (AR) applications is the interference of virtually displayed objects in the user's visual field, with the current attentional focus of the user. Newly generated content can disrupt internal thought processes. If we can detect such internally-directed attention periods, the interruption could either be avoided or even used intentionally. In this work, we designed a special alignment task in AR with two conditions: one with externally-directed attention and one with internally-directed attention. Apart from the direction of attention, the two tasks were identical. During the experiment, we performed a 16-channel EEG recording, which was then used for a binary classification task. Based on selected band power features, we trained a Linear Discriminant Analysis classifier to predict the label for a 13-s window of each trial. Parameter selection, as well as the training of the classifier, were done in a person-dependent manner in a 5-fold cross-validation on the training data. We achieved an average score of approximately 85.37% accuracy on the test data (± 11.27%, range = [66.7%, 100%], 6 participants > 90%, 3 participants = 100%). Our results show that it is possible to discriminate the two states with simple machine learning mechanisms. The analysis of additionally collected data dispels doubts that we classified the difference in movement speed or task load. We conclude that a real-time assessment of internal and external attention in an AR setting in general will be possible.
Therapeutic inhibition of Mcl-1 blocks cell survival in estrogen receptor-positive breast cancers

Cancers often overexpress anti-apoptotic Bcl-2 proteins for cell death evasion, a recognized hallmark of cancer progression. While estrogen receptor (ER)-α+ breast cancers express high levels of three anti-apoptotic Bcl-2 family members (Bcl-2, Bcl-xL, and Mcl-1), pharmacological inhibition of Bcl-2 and/or Bcl-xL fails to induce cell death in ERα+ breast cancer cell lines, due to rapid and robust Mcl-1 upregulation. The mechanisms of acute Mcl-1 upregulation in response to Bcl-2/Bcl-xL inhibition remain undefined in in ERα+ breast cancers. We report here that blockade of Bcl-2 or Bcl-xL, alone or together, rapidly induced mTOR signaling in ERα+ breast cancer cells, rapidly increasing cap-dependent Mcl-1 translation. Cells treated with a pharmacological inhibitor of cap-dependent translation, or with the mTORC1 inhibitor RAD001/everolimus, displayed reduced protein levels of Mcl-1 under basal conditions, and failed to upregulate Mcl-1 protein expression following treatment with ABT-263, a pharmacological inhibitor of Bcl-2 and Bcl-xL. Although treatment with ABT-263 alone did not sustain apoptosis in tumor cells in culture or in vivo, ABT-263 plus RAD001 increased apoptosis to a greater extent than either agent used alone. Similarly, combined use of the selective Mcl-1 inhibitor VU661013 with ABT-263 resulted in tumor cell apoptosis and diminished tumor growth in vivo. These findings suggest that rapid Mcl-1 translation drives ABT-263 resistance, but can be combated directly using emerging Mcl-1 inhibitors, or indirectly through existing and approved mTOR inhibitors.
Similar Shift Patterns in Gut Bacterial and Fungal Communities Across the Life Stages of Bactrocera minax Larvae From Two Field Populations

Bactrocera minax (Enderlein) (Diptera: Tephritidae) is an oligophagous insect pest that damages citrus fruit, especially in China. Due to larvae living within a highly septic environment, a wide variety of microorganisms exist in the larval gut of B. minax. However, a systematic study of the intestinal microbiota of this harmful insect pest is still lacking. Here, we comprehensively investigated the larval gut microbiota of B. minax in two field populations from Zigui (developed in orange) and Danjiangkou (developed in mandarin orange). We observed a dominance of Proteobacteria and Firmicutes in these bacterial communities, and Enterobacteriaceae was the predominant family throughout the larval stage. However, most of the identified fungal sequences were annotated as being from either Ascomycota or Basidiomycota phyla. Although there was a difference in the structure of the microbial communities between the two populations, the dynamic change patterns of most of the members of the microbiota were similar across the lifespan of larvae in both populations. The relative abundances of the Acetobacteraceae, Leuconostocaceae, and Lactobacillaceae gut bacteria as well as the Pichiaceae, Sebacinaceae, and Amanitaceae fungi increased throughout development, and these microorganisms stably resided in the larval gut. Furthermore, the dynamic changes of the functions of gut bacterial communities were inferred, and there was a significant increase in carbohydrate metabolism across the lifespan of larvae in both groups. Spearman correlation analysis showed that Acetobacteraceae, Lactobacillaceae, and Leuconostocaceae displayed a positive correlation with fructose and mannose metabolism, an important pathway of carbohydrate metabolism, highlighting the potential roles of these prevalent microbial communities in host biology.
Control Scheme for a Fractional-Order Chaotic Genesio-Tesi Model

In this paper, based on the earlier research, a new fractional-order chaotic Genesio-Tesi model is established. The chaotic phenomenon of the fractional-order chaotic Genesio-Tesi model is controlled by designing two suitable time-delayed feedback controllers. With the aid of Laplace transform, we obtain the characteristic equation of the controlled chaotic Genesio-Tesi model. Then by regarding the time delay as the bifurcation parameter and analyzing the characteristic equation, some new sufficient criteria to guarantee the stability and the existence of Hopf bifurcation for the controlled fractional-order chaotic Genesio-Tesi model are derived. The research shows that when time delay remains in some interval, the equilibrium point of the controlled chaotic Genesio-Tesi model is stable and a Hopf bifurcation will happen when the time delay crosses a critical value. The effect of the time delay on the stability and the existence of Hopf bifurcation for the controlled fractional-order chaotic Genesio-Tesi model is shown. At last, computer simulations check the rationalization of the obtained theoretical prediction. The derived key results in this paper play an important role in controlling the chaotic behavior of many other differential chaotic systems.
Context-aware Anomaly Detector for Monitoring Cyber Attacks on Automotive CAN Bus

Automotive electronics is rapidly expanding. An average vehicle contains million lines of software codes, running on 100 of electronic control units (ECUs), in supporting number of safety, driver assistance and infotainment functions. These ECUs are networked using a Controller Area Network (CAN). Security of the CAN bus has not historically been a major concern, however, recent research demonstrate that CAN has many vulnerabilities to cyber attacks. This paper presents a contextualised anomaly detector for monitoring cyber attacks on the CAN bus. Proposed algorithm is based on message sequence modelling, using so called N-grams distributions. It utilises only benign data (one class) for training and threshold estimation. Performance of the algorithm was tested against two different attack scenarios, RPM and gear gauge messages spoofing, using data captured from a real vehicle. Experimental outcomes demonstrate that proposed algorithm is capable of detecting both attacks with %100 accuracy, using far smaller time windows (100ms) which is essential for a practically deployable automotive cyber security solution.
Performance Improvement of a Compound Helicopter Rotor Head by Aerodynamic Shape Optimization

Within the present publication, the rotor head of a compound helicopter known as Rapid And Cost-Effective Rotorcraft (RACER) is investigated. In particular, the aerodynamic design optimization of the RACER blade-sleeve fairings is conducted. For this purpose, an isolated rotor head is generated featuring a full-fairing beanie, the blade-sleeve fairing and a truncated rotor blade. Moreover, a steady rotor is investigated and averaged flow conditions according to the RACER cruise flight are applied. The automated aerodynamic design optimization is performed by means of a previously developed optimization tool chain. A global multi-objective genetic optimization algorithm is applied for the given problem. During preliminary work, a two-dimensional aerodynamic design optimization of selected blade-sleeve sections was conducted. These optimized airfoils represent the design variables for the current optimization problem. The shape modification of the three-dimensional fairing is realized by exchanging specific airfoils at certain spanwise sections.
Detecting Discourse-Independent Negated Forms of Public Textual Cyberbullying

Cyberbullying is a risk associated with the online safety of young people and, in this paper, we address one of its most common implicit forms – negation-based forms. We first describe the role of negation in public textual cyberbullying interaction and identify the cyberbullying constructions that characterise these forms. We then formulate the overall detection mechanism which captures the three necessary and sufficient elements of public textual cyberbullying – the personal marker, the dysphemistic element, and the link between them. Finally, we design rules to detect both overt and covert negation-based forms, and measure their effectiveness using a development dataset, as well as a novel test dataset, across several metrics: accuracy, precision, recall, and the F1-measure. The results indicate that the rules we designed closely resemble the performance of human annotators across all measures.
Collaborative Energy-Efficient Moving in Internet of Things: Genetic Fuzzy Tree Versus Neural Networks

The sensing application of space surveillance has put forward challenges to the Internet of Things (IoT). However, current moving algorithms in IoT rarely aim for target surveillance. In view of energy efficiency for multimodal signals in IoT, this paper mainly investigate three typical target trajectories: 1) line; 2) square; and 3) circle. On a basis of target learning, two types of collaborative sensor movement algorithms are proposed and compared. One approach is based on genetic fuzzy tree (GFT) and the other is based on the neural network (NN). Both algorithms can balance the energy consumption and the tracking performance. Simulation results show that the GFT-based algorithm outperforms NN-based algorithm in tracking error, but it demands more computational cost than that of NN-based scheme. This important result can provide intellectual sensing support in IoT applications, such as target surveillance, anti-terrorism, and unmanned border awareness.
Adsorption and desorption behavior of atrazine on Carbon Nanotubes

In this paper,the adsorption and desorption of atrazine(AT)on single-walled carbon nanotubes(SWNT)and multi-walled carbon nanotubes(MWNT)in aqueous solution were studied in batch reactors.The results showed that the ionic strength had no significant influence on the adsorption of AT onto SWNT and MWNT.With the increase of pH,the adsorption of AT onto the two nanomaterials increased greatly,which indicated that the speciation of atrazine was the dominant factor controlling the adsorption capacity.The adsorption-desorption curves revealed that no significant desorption hysteresis existed under the conditions of this study.High adsorption capacity and adsorption reversibility of atrazine on carbon nanotubes(CNTs)imply that CNTs could result in health and environmental risks when applied on a large scale.
Research on the synthetic method of ink painting based on convolutional neural network

In this paper, we defined a characteristic response of convolutional layer mapping in a convolutional neural network model, and explored correlation between them by adjusting a trained convolutional neural network model’s structure. First of all, we did pre-processing include contrastive enhancement for photos. Then matched the photo's characteristic response to obtain its content information in a random image. And matched correlation between the characteristic responses of ink painting again to obtain its style information. The final step was to synthesize the image. Traditional ink painting method usually generate images with some basic features. So a particular style can’t be assigned, even generating stiff images without artistic conception. Aim at these situations, this paper proposes an ink painting synthesis methods based on convolutional neural network, which can produce better images. It retains both outline information of original photo and overall texture information of ink painting. This paper also presents a method ,which can merge ink painting style into a photo. The method works well in synthesizing grayscale image such as ink painting.
Development of Multi-Spectral Thermometer for Explosion Flame True Temperature Measurement——Field Experiments and Measurement Accuracy Analysis

In the present article,the measurement principle of a multi-target multi-spectral thermometer developed previously is improved in that the brightness temperature approximation method is adopted to overcome the second measurement method initial value selection difficulty.The thermometer is used to measure the explosion true temperature of 3KG TNT explosive in open fields.The experimental results show that this pyrometer can measure changes in the explosion flame true temperature in the whole process,and functions well in the wavefront instantaneous temperature measurement and burning fireball temperature measurement.Finally,through the analysis of the factors which affect the thermometer measurement accuracy,it was concluded that the main error sources restricting the measurement accuracy improvement are still the true temperature algorithm error and the calibration method error.The analysis result has provided the direction for the high-precision thermometer development.
Parameters and forces of a PM linear synchronous motor with magnetic guides for industrial applications: computed and experimental results

A novel type of linear motor characterized by two stators and one ironless cursor, double side ironless motor (DSILM), has been designed. The motor has been designed to drive autonomous complete contactless transportation systems, equipped with a magnetic levitation system. Applications of these systems can be found in ultra clean and maintenance free rooms or where wear and maintenance would cause expensive plant stops, The design have been performed integrating traditional formulae and the 2D and 3D FEM simulations. In particular, the evaluation of the normal force generated by this kind of motor can only be done performing FEM analyses. A test bench with a linear motor prototype as been constructed and an experimental validation of the design results has been performed. The experimental tests have been performed in order to evaluate the model parameters, the field distribution and the propulsion force. In the paper, the design procedure and the comparisons between the design predictions and the experimental results are presented.
A low complexity automatic white balance algorithm for AMOLED hardware driving using histogram shifting with compensation

ABSTRACT Automatic white balance (AWB) is one of the most important functions for display devices. As to active-matrix organic light-emitting diode (AMOLED) driving, it not only needs reasonable colour cast correcting results, but also require high power efficiency. In the existing techniques, the power constraint is achieved resource-costly, and has not been applied in AWB algorithms. This article proposes an AWB algorithm combined with simple power constraint method and excellent colour cast correcting ability. Without the part of computing coefficients in conventional AWB algorithms, and replacing most of multiplications with additions, the computational complexity of the proposed algorithm is reduced. The experimental results show that the proposed algorithm is competitive with that of state-of-the-art AWB algorithms and the value of power dissipation for the images processed by the proposed algorithm is 33.76%, 19.95% and 41.26% smaller than grey-world (GW), white-patch (WP) and colour histogram stretching (CHS) algorithm, respectively. The proposed algorithm can also be implemented in AMOLED driving owing to its low computational complexity. AbbreviationPower Constraint(PD)