Miracle-dz/UniFAR-FTUs huggingface dataset:
Phase space scales of free energy dissipation in gradient-driven gyrokinetic turbulence

A reduced four-dimensional (integrated over perpendicular velocity) gyrokinetic model of slab ion temperature gradient-driven turbulence is used to study the phase-space scales of free energy dissipation in a turbulent kinetic system over a broad range of background gradients and collision frequencies. Parallel velocity is expressed in terms of Hermite polynomials, allowing for a detailed study of the scales of free energy dynamics over the four-dimensional phase space. A fully spectral code – the DNA code – that solves this system is described. Hermite free energy spectra are significantly steeper than would be expected linearly, causing collisional dissipation to peak at large scales in velocity space even for arbitrarily small collisionality. A key cause of the steep Hermite spectra is a critical balance – an equilibration of the parallel streaming time and the nonlinear correlation time – that extends to high Hermite number n. Although dissipation always peaks at large scales in all phase space dimensions, small-scale dissipation becomes important in an integrated sense when collisionality is low enough and/or nonlinear energy transfer is strong enough. Toroidal full-gyrokinetic simulations using the Gene code are used to verify results from the reduced model. Collision frequencies typically found in present-day experiments correspond to turbulence regimes slightly favoring large-scale dissipation, while turbulence in low-collisionality systems like ITER and space and astrophysical plasmas is expected to rely increasingly on small-scale dissipation mechanisms. This work is expected to inform gyrokinetic reduced modeling efforts like Large Eddy Simulation and gyrofluid techniques.
SCN2A- Associated Episodic and Persistent Ataxia with Cerebellar Atrophy: A Case Report

SCN2A, a gene that codes for a sodium channel highly expressed in the cerebellum, has been linked to a heterogeneous phenotype, including episodic ataxia (EA) and epilepsy, among other symptoms1. Given the rarity of SCN2A-associated EA and its recent description, it is important the genotype-phenotype relationship of SCN2A-associated EA be better defined for prognosis and optimizing future management. Thus, we describe a 2-year-old boy with a SCN2A variant causing an initial prolonged episode of profound ataxia lasting 4 months, cerebellar atrophy, and persistent mild ataxia with episodic exacerbations. Due to the patient’s lack of early epilepsy, prolonged initial episode of ataxia, and cerebellar atrophy, this case broadens the scope of the SCN2A variant phenotype. SCN2A should be considered as a cause of early onset ataxia in children with targeted testing or as part of Whole Exome Sequencing (WES) in patients with new onset persistent or EA with or without seizures.
On the Convective and Absolute Nature of Instabilities in Finite Difference Numerical Simulations of Open Flows

In numerical simulations of unstable flows the absolute or convective nature of the instability can be modified by numerical effects. We introduce a convective/absolute analysis of the dispersion relations associated with discretized operators. This analysis leads to conditions on the discretization parameters in order to avoid numerical transition from absolute to convective instability and vice versa. In numerical simulations of non-parallel flows, local numerical transitions, of the kind described in this paper, could lead to the wrong global dynamics.
Knockout of Rlim Results in a Sex Ratio Shift toward Males but Superovulation Cannot Compensate for the Reduced Litter Size

Simple Summary Maternal Rlim is required for imprinted X-chromosome inactivation (XCI), which is essential for normal development of female mouse embryos. In this study, we used a novel approach to inactivate the maternal Rlim allele in female embryos, resulting in a male sex-ratio shift in the offspring. However, the reduced litter size caused by the loss of female embryos could not be compensated for by superovulation in the mother mice. The present study develops a new approach to select offspring sex according to the difference in Rlim function between male and female mouse embryos. This gender control approach may help to improve the productivity in livestock and prevent the sex-associated hereditary diseases in humans. Abstract Technologies that can preselect offspring gender hold great promise for improving farm animal productivity and preventing human sex-related hereditary diseases. The maternal Rlim allele is required for imprinted X-chromosome inactivation, which is essential for the normal development of female mouse embryos. In this study, we inactivated the maternal Rlim allele in embryos by crossing a male transgenic mouse line carrying an X-linked CMV-Cre transgene with a female line carrying a loxP-flanked Rlim gene. Knockout of the maternal Rlim gene in embryos resulted in a male-biased sex ratio skew in the offspring. However, it also reduced litter size, and this effect was not compensated for by superovulation in the mother mice. In addition, we showed that siRNA-mediated knockdown of Rlim in mouse embryos leads to the birth of male-only progenies. This study provides a new promising method for male-biased sex selection, which may help to improve the productivity in livestock and prevent sex-associated hereditary diseases in humans.
A New Strategy for Nucleic Acid Delivery and Protein Expression Using Biocompatible Nanohydrogels of Predefined Sizes

We have developed new formulations of nanohydrogels (NHGs) complexed with DNA devoid of cell toxicity, which, together with their tuned sizes, makes them of great interest for delivering DNA/RNA for foreign protein expression. Transfection results demonstrate that, unlike classical lipo/polyplexes, the new NHGs can be incubated indefinitely with cells without apparent cellular toxicity, resulting in the high expression of foreign proteins for long periods of time. Although protein expression starts with a delay as compared to classical systems, it is sustained for a long period of time, even after passing cells without observation of toxicity. A fluorescently labelled NHG used for gene delivery was detected inside cells very early after incubation, but the protein expression was delayed by many days, demonstrating that there is a time-dependent release of genes from the NHGs. We suggest that this delay is due to the slow but continuous release of DNA from the particles concomitantly with slow but continuous protein expression. Additionally, results obtained after the in vivo administration of m-Cherry/NHG complexes indicated a delayed but prolonged expression of the marker gene in the tissue of administration. Overall, we have demonstrated gene delivery and foreign protein expression using GFP and m-Cherry marker genes complexed with biocompatible nanohydrogels.
A simple, pipette-free, and power-free device for virus nucleic acid detection

A portable, inexpensive, and easy-to-manufacture microfluidic device is developed for the detection of SARS-CoV-2 dsDNA fragments. In this device, four reaction chambers separated by carbon fiber rods are pre-loaded with isothermal amplification and CRISPR-Cas12a reagents. The reaction is carried out by simply pulling the rods, without the need for manual pipetting. To facilitate power-free pathogen detection, the entire detection is designed to be heated with a disposable hand warmer. After the CRISPR reaction, the fluorescence signal generated by positive samples is identified by naked eye, using an inexpensive flashlight. This simple and sensitive device will serve as a new model for the next-generation viral diagnostics in either hospital or resource-limited settings.
Spatiotemporal Regulation of FMNL2 by N-Terminal Myristoylation and C-Terminal Phosphorylation Drives Rapid Filopodia Formation

The actin nucleating and polymerizing formin-like 2 (FMNL2) is upregulated in several cancers and has been shown to play important roles in cell migration, invasion, cell–cell adhesion and filopodia formation. Here, using structured illumination microscopy we show that FMNL2 promotes rapid and highly dynamic filopodia formation in epithelial cells while remaining on the tip of the growing filopodia. This filopodia tip localization depends fully on its N-terminal myristoylation. We further show that FMNL2-dependent filopodia formation requires its serine 1072 phosphorylation within the diaphanous-autoregulatory domain (DAD) by protein kinase C (PKC) α. Consistent with this, filopodia formation depends on PKC activity and PKCα localizes to the base of growing filopodia. Thus, a PKCα–FMNL2 signaling module spatiotemporally controls dynamic filopodia formation.
Extraction of underlying rules by projection pursuit learning networks with M-apoptosis structural learning algorithm

In order to extract simple rules from observed samples, we introduce the PPLN with RBF to represent the relationship between inputs and outputs in a low-dimensional projected space, and propose a structural learning method for the PPLN. We consider three kinds of penalty terms to eliminate the dimensionality, the input variables and hidden units of PPLN. In our method, Minkowski norms of the first order derivatives of the network with respect to input variables, the elements of projection vectors and the weight parameters, are used as the penalty terms. Simple rules are extracted from the PPLN by eliminating the unnecessary links and units.
Size and shape control of sub-20 nm patterns fabricated using focused electron beam-induced processing

Abstract. In a first study to analyze the feasibility of electron beam-induced deposition (EBID) for creating certain patterns in advanced lithography, line patterns were fabricated on silicon wafers using EBID. The growth conditions were such that the growth rate is fully determined by the electron flux (the current limited growth regime). It is experimentally verified that different patterning strategies, such as serial versus parallel patterning and single pass patterning versus multiple pass patterning, all lead to the same result in this growth regime. Images of EBID lines, imaged in a scanning electron microscope, were analyzed to determine the position of the lines, the width of the lines, and the linewidth roughness (LWR). The results are that the lines have an average width of 13.7 nm, an average standard deviation of 1.6 nm in the center position of the lines, and an average LWR of 4.5 nm (1σ value). As an example of the capabilities of EBID, a logic-resembling lithography pattern was fabricated.
Polygons and gravitons

1. There has been much interest recently in ‘instantons’. These correspond, in differential geometric terms, to connexions in principal bundles over Euclidean 4-space whose curvature satisfies the Yang-Mills equations. The connexion is also required to approach the trivial connexion at infinity. The self-dual solutions have been classified by converting the problem into one of algebraic geometry using the ideas of R. Penrose and R. Ward
Machine Learning Applied to Public Transportation by Bus: A Systematic Literature Review

Machine learning (ML) solutions have been proposed to make public transportation more attractive. Works that employ ML in bus transportation focus on various problems, such as travel time prediction or passenger flow prediction. These solutions look to improve elements of transportation services, such as the availability of information on passengers’ travel time and the reliability and regularity of the service. An analysis of the solutions proposed in the literature for public transportation by bus can reveal opportunities for data scientists and transportation professionals, and highlight problems that have been only slightly explored. In addition, mapping information about modeling these solutions (e.g., types of data produced by devices on the transportation network, which can be used in modeling a solution) could help beginner data scientists develop public transportation solutions. Transportation professionals can benefit from an overview of possible transportation solutions to improve transportation problems and direct government agency efforts to implement these solutions. This paper presents a survey of ML-based solutions for public bus transportation and details the modeling of these solutions (e.g., data types, ML algorithms). In addition, the problems tackled in the literature are categorized into four themes, and the solutions proposed to deal with them are schematized, highlighting problems that are little explored.
Combination Therapies Targeting Apoptosis in Paediatric AML: Understanding the Molecular Mechanisms of AML Treatments Using Phosphoproteomics

Paediatric acute myeloid leukaemia (AML) continues to present treatment challenges, as no “standard approach” exists to treat those young patients reliably and safely. Combination therapies could become a viable treatment option for treating young patients with AML, allowing multiple pathways to be targeted. Our in silico analysis of AML patients highlighted “cell death and survival” as an aberrant, potentially targetable pathway in paediatric AML patients. Therefore, we aimed to identify novel combination therapies to target apoptosis. Our apoptotic drug screening resulted in the identification of one potential “novel” drug pairing, comprising the Bcl-2 inhibitor ABT-737 combined with the CDK inhibitor Purvalanol-A, as well as one triple combination of ABT-737 + AKT inhibitor + SU9516, which showed significant synergism in a series of paediatric AML cell lines. Using a phosphoproteomic approach to understand the apoptotic mechanism involved, proteins related to apoptotic cell death and cell survival were represented, in agreement with further results showing differentially expressed apoptotic proteins and their phosphorylated forms among combination treatments compared to single-agent treated cells such upregulation of BAX and its phosphorylated form (Thr167), dephosphorylation of BAD (Ser 112), and downregulation of MCL-1 and its phosphorylated form (Ser159/Thr 163). Total levels of Bcl-2 were decreased but correlated with increased levels of phosphorylated Bcl-2, which was consistent with our phosphoproteomic analysis predictions. Bcl-2 phosphorylation was regulated by extracellular-signal-regulated kinase (ERK) but not PP2A phosphatase. Although the mechanism linking to Bcl-2 phosphorylation remains to be determined, our findings provide first-hand insights on potential novel combination treatments for AML.
A novel approach based on bio‐inspired efficient clustering algorithm for large‐scale heterogeneous wireless sensor networks

In large‐scale heterogeneous wireless sensor networks (WSNs), clustering is particularly significant for lowering sensor nodes (SNs) energy consumption and creating algorithm more energy efficient. The selection of cluster heads (CHs) is a crucial task in the clustering method. In this paper, optimised K‐means clustering algorithm and optimised K‐means based modified intelligent CH selection based on BFOA for large‐scale network (lar‐OK‐MICHB) is hybridised for CH selection process. Here, we utilised the extended capabilities of OK‐MICHB algorithm for large‐scale network. Furthermore, in many applications where energy is a primary constraint, such as military surveillance and natural disaster prediction, the stability region is also a significant factor, with a longer network lifespan being a primary requirement. In the proposed approach, only the CH selection is made after every round in place of cluster and CH change as done in conventional hierarchical algorithm. The simulation results reveal that, while keeping the distributive structure of WSNs, suggested lar‐OKMIDEEC can locate real greater leftover energy nodes for selection of CH without utilising randomise or estimated procedures. Furthermore, as compared with the multi‐level MIDEEC protocol, this offers a larger stability region with 68.96% increment, more consistent selection of CH in every round, and greater packets (i.e., in numbers) received at the base station (BS) with a longer network lifetime with 327% increment.
Optimized EWT-Seq2Seq-LSTM with Attention Mechanism to Insulators Fault Prediction

Insulators installed outdoors are vulnerable to the accumulation of contaminants on their surface, which raise their conductivity and increase leakage current until a flashover occurs. To improve the reliability of the electrical power system, it is possible to evaluate the development of the fault in relation to the increase in leakage current and thus predict whether a shutdown may occur. This paper proposes the use of empirical wavelet transform (EWT) to reduce the influence of non-representative variations and combines the attention mechanism with a long short-term memory (LSTM) recurrent network for prediction. The Optuna framework has been applied for hyperparameter optimization, resulting in a method called optimized EWT-Seq2Seq-LSTM with attention. The proposed model had a 10.17% lower mean square error (MSE) than the standard LSTM and a 5.36% lower MSE than the model without optimization, showing that the attention mechanism and hyperparameter optimization is a promising strategy.
Normothermic ex vivo heart perfusion with NLRP3 inflammasome inhibitor Mcc950 treatment improves cardiac function of circulatory death hearts after transplantation

Background The utilization of donation after circulatory death (DCD) hearts can enlarge the donor pool. However, DCD hearts suffer from serious ischemia/reperfusion injury (IRI). Recent studies found that the activation of NLRP3 inflammasome could play a significant role in organ IRI. Mcc950, which is a novel inhibitor of the NLRP3 inflammasome, can be applied to treat various kinds of cardiovascular diseases. Therefore, we hypothesized that the treatment of mcc950 could protect DCD hearts preserved with normothermic ex vivo heart perfusion (EVHP) against myocardial IRI via inhibiting NLRP3 inflammasome in a rat heart transplantation model of DCD. Methods Donor-heart rats were randomly divided into four groups: Control group; Vehicle group; MP-mcc950 group; and MP + PO-mcc950 group. Mcc950 was added into the perfusate of normothermic EVHP in the MP-mcc950 and MP + PO-mcc950 groups, and was injected into the left external jugular vein after heart transplantation in the MP + PO-mcc950 group. Cardiac functional assessment was performed. The level of oxidative stress, inflammatory response, apoptosis, and NLRP3 inflammasome-associated protein of donor hearts were evaluated. Results The treatment with mcc950 significantly increased the developed pressure (DP), dP/dtmax, and dP/dtmin of the left ventricular of DCD hearts at 90 min after heart transplantation in both MP-mcc950 and MP + PO-mcc950 groups. Furthermore, mcc950 added into perfusate and injected after transplantation in both MP-mcc950 and MP + PO-mcc950 groups significantly attenuated the level of oxidative stress, inflammatory response, apoptosis, and NLRP3 inflammasome compared with the vehicle group. Conclusions Normothermic EVHP combined with mcc950 treatment can be a promising and novel DCD heart preservation strategy, which can alleviate myocardial IRI via inhibiting NLRP3 inflammasome.
Laser speckle effects on hard target differential absorption lidar

Reflection of laser light from a diffuse surface exhibits a complex interference pattern known as laser speckle. Measurement of the reflected intensity from remote targets, common to `hard-target' differential absorption lidar, requires consideration of the statistical properties of the reflected light. We have explored the effects of laser speckle on the noise statistics for CO2 DIAL. For an ensemble of independent speckle patterns it is predicted that the variance for the measured intensity is inversely proportional to the number of speckle measured. We have used a rotating drum target to obtain a large number of independent speckle and have measured the predicted decrease in the variance after correlations due to system drifts were removed. Measurements have been made using both circular and linear polarized light. These measurements show a slight improvement in return signal statistics when circular polarization is used. We have conducted experiments at close range to isolate speckle phenomena from other phenomena, such as atmospheric turbulence and platform motion thus allowing us to gain a greater understanding of speckle issues. We have also studied how to remove correlation in the data caused by albedo inhomogenuties producing a more statistically independent ensemble of speckle patterns. We find that some types of correlation are difficult to remove from the data.
Opportunities and challenges for MEMS in lightwave communications

Over the remarkably short interval of just a few years, optical microelectromechanical systems (MEMS) have breached the gulf from laboratory curiosity to advanced development and early trial deployment in lightwave-communications systems. This owes largely to the ease with which the technology has demonstrated high optical quality and reasonably fast tuning and switching subsystems that are compact and potentially low in cost. Lightwave micromachines now threaten to make possible functional structures for building tunable lasers and filters, dynamic gain-equalizers, chromatic dispersion-compensators, wavelength-add-drop multiplexers, and polarization-controllers that represent substantial improvements over the conventional state of the art. More extravagant yet, both in promise and in expectations, is the potential of MEMS as a means of building the large-port-count optical switches that are just now becoming needed by emerging mesh-based core transport networks. In this paper, we review the current status and prospects for MEMS in lightwave communications, with particular emphasis on high-port-count core optical cross connects, and discuss challenges that still confront this technology.
A Flipped Systematic Debugging Approach to Enhance Elementary Students’ Program Debugging Performance and Optimize Cognitive Load

Reintroducing computer science (CS) education in K–12 schools to promote computational thinking (CT) has attracted significant attention among scholars and educators. Among the several essential components included in CS and CT education, program debugging is an indispensable skill. However, debugging teaching has often been overlooked in K–12 contexts, and relevant empirical studies are lacking in the literature. Moreover, novices generally have poor performance in domain knowledge and strategic knowledge concerning debugging. They also consistently experience a high cognitive burden in debugging learning. To address these gaps, we developed a flipped systematic debugging approach combined with a systematic debugging process (SDP) and the modeling method. A quasi-experimental study was conducted to explore the effectiveness of this flipped systematic debugging approach, in which 83 fifth-grade students attended the flipped debugging training lessons with the SDP–modeling method, and 75 fifth-grade students attended the unassisted flipped debugging training lessons without the SDP–modeling method. The results indicated that flipped debugging training using the SDP–modeling method improved students’ debugging skills. The results from the questionnaire showed that the proposed teaching approach increased the students’ investment in germane cognitive load by promoting schema construction. It also helped reduce students’ intrinsic and extraneous cognitive load in learning.
Asynchronous Slepian-Wolf coding via source-splitting

The Slepian-Wolf coding problem for two sources is considered. It is known that vertices of the Slepian-Wolf region can be achieved with a complexity which is significantly lower than that of a general point and do not require that encoders are synchronized. It is shown that by splitting a source into two virtual sources one can reduce the problem of coding an arbitrary point to that of coding a vertex of a three-dimensional Slepian Wolf region. This approach generalizes to arbitrary number of sources.